#Shopify developer Boston

[pluginhiveblogs]

Shopify Shipping with Canpar Express

Discover Seamless Shipping Solutions with Canpar Express for Your Shopify Store! 📦 Since its acquisition by TransForce in 2002, Canpar has significantly expanded its shipping capabilities, offering dependable parcel tracking services to eCommerce brands within Canada and across North America.

Shipping Services Offered by Canpar Express

Express Shipping: Ideal for urgent shipments requiring delivery by the next business day. Canpar Express also offers a special service for collecting payments with express shipments.

SelectPak: A Canpar Express polybag designed for smaller items and documents, offering country-wide shipping within one to three business days. Collect payment service is available for SelectPak shipments as well.

SelectParcel: Tailored for larger parcels with guaranteed on-time delivery. Customers provide the box while Canpar supplies the shipping label.

Ground Shipping: A trackable and cost-efficient option with delivery within one to four business days. Customers can also schedule pickups for added convenience.

Canpar Express International Shipping to US and Other Countries

Canpar provides a transit time map on its website, outlining estimated shipping durations to the USA and select international destinations. For instance, shipping from Vancouver to Boston takes approximately seven business days, while Toronto to Detroit typically takes three business days. Canpar also offers rush shipping guarantees to specific cities, ensuring timely delivery.

Additionally, Canpar offers various add-on services for shipments, including COD (cash on delivery), Chain of Signature, Pickup on Demand, Collect services, Pickup tags, and return tag services. Premium services such as 10 am, noon, and Saturday delivery options are also available for added convenience.

Automating the Canpar Express Shipping Process for Shopify

Integrating Canpar Express with Shopify is seamless with the Shopify Multi-Carrier Shipping Label Appfrom PluginHive. This cost-effective app eliminates the need for expensive web development, allowing businesses to offer customers shipping rates from multiple couriers at checkout. In conclusion, leveraging Canpar Express for eCommerce shipping needs offers businesses a reliable and efficient solution, backed by a wide range of services and integration options to streamline operations and enhance customer satisfaction.

[aidorobot]

Freedom Robotics Launches With $6.6M In Seed Funding To Build The ‘AWS Equivalent For Robotics’

Jibo, a social robot meant to compete with Amazon’s Alexa, was vocal amid its shut down. It told owners, “maybe someday when robots are way more advanced than today, and everyone has them in their homes, you can tell yours that I said hello.”

Before shutting down its robots, the Boston company raised around $72.7 million in funding, according to Crunchbase. Burning cash isn’t singular to this robot, however. Robotics startup Anki, which raised $200 million in funding over time, shut down in April. And as for Alexa competitor Aido, you probably haven’t heard of it, and that’s probably because it was kicked off Indiegogo and StartupEngine.

Read More:-

So it is clear that it is hard to be a robotics startup. And one was started to make it easier. Freedom Robotics launched out of stealth yesterday with $6.6 million in funding to help build the “AWS equivalent for robotics.” The San Francisco company offers a suite of tools and services so robotics companies can go to the market faster, as well as smarter.

The round was led by Initialized Capital. Other investors include Toyota AI Ventures, Liquid 2 Ventures, and Green Cow Venture Capital. Also, a slew of individuals participated in the round, including Andrew Miklas, Justin Kan, and Arianna Simpson.

According to CEO and co-founder Joshua Wilson, Freedom Robotics will help other startups succeed.

“This is like trying to create a new software startup and writing your own database from scratch as the first step, or starting an e-commerce brand and having to build your own shopping cart instead of using Shopify,” said Wilson. “We saw this countless times in other markets and companies taking this strategy this got burnt out just trying to get into the market. Then quickly were outpaced by competition. Then they ran out of money. It’s absolutely crazy.”

Him and his co-founders saw a status quo in robotics: “It takes months and sometimes years of work before a prototype can be in a customers hands.” Plus, he added, speed and execution seem to be the “determining factor for most companies that win.”

After interviewing over 50 robotics developers and founders, they decided to create infrastructure and tooling pieces to help other robotics companies succeed.

Read More:- Arshad Hisham

For example, if something goes wrong, non-technical team members can use Freedom Robotics code to get alerts about an issue. Similar to a black box on an airplane, the team can see a replay of what went wrong and then collaborate between operators, developers, and managers to get things fixed quickly.

From the technical side, Williams says operators can control a robot from afar. For example making a delivery robot get to safety. You can also use Freedom Robotics to see the health status of a fleet of thousands of robots, to help inform decisions around maintenance and service.

The company did declined to disclose information around customers, however it claims it is being used by robots across various industries including agriculture, restaurants, warehouse factories, and last mile delivery networks.

The thought is, Wilson tells me, that by lowering the barrier to entry there is “a more diverse pool of companies bringing robotics into the mainstream.” He would know how important that is. Before launching Freedom Robotics, he started a company that was meant to build robots. And even got “several term sheet offers.” Despite good traction, Wilson thought the fundamentals in robot creation might be the more pressing market.

So while Freedom Robotics might be a company too late to save Jibo, Anki, and Aido and the rest of the deceased, the thought here is that it could help future companies have an easier time not just kickstarting, but also staying alive.

Click Here:-Ingen Dynamics

[thedigitalhunt]

Mastering Shopify: A Comprehensive Guide to Web Development

Introduction:

When it comes to Shopify web development, finding the right partner can make all the difference in building a successful online store. In this article, we will explore the key aspects of mastering Shopify web development and highlight why The Digital Hunt stands out as the best Shopify development company in Boston and Cincinnati, USA. With their expertise in Shopify development services, app development, and website development, The Digital Hunt has established itself as a top-notch Shopify development agency.

Shopify Development Services:

The Digital Hunt offers a wide range of Shopify development services tailored to meet the unique needs of businesses. Their team of skilled professionals excels in creating custom Shopify websites that are visually appealing, user-friendly, and optimized for conversion. Whether you need a brand new online store or want to enhance an existing one, The Digital Hunt can deliver exceptional results.

Shopify App Development:

With the increasing demand for advanced functionality and seamless integration, Shopify app development has become crucial for online businesses. The Digital Hunt's expert developers have extensive experience in creating powerful Shopify apps that extend the platform's capabilities and provide unique features to enhance the user experience. Their proficiency in Shopify app development ensures that businesses can leverage the full potential of the platform.

Shopify Web Development:

The Digital Hunt takes pride in its team of highly skilled Shopify web developers who possess in-depth knowledge and expertise in the platform. From customizing themes and templates to implementing complex functionalities, their developers have the proficiency to tackle any Shopify web development project. Their attention to detail and commitment to delivering exceptional results make them the go-to choice for businesses seeking professional Shopify web development services.

Shopify Website Development:

A visually appealing and functional website is crucial for success in the competitive e-commerce landscape. The Digital Hunt specializes in Shopify website development, creating stunning online stores that capture the essence of a brand and engage visitors. Their expertise in user experience design, responsive web development, and mobile optimization ensures that businesses can deliver a seamless shopping experience to their customers across all devices.

Conclusion:

When it comes to mastering Shopify web development, The Digital Hunt emerges as the best choice for businesses in Boston and Cincinnati, USA. With their comprehensive range of Shopify development services, expertise in app development, and proficiency in website development, they are well-equipped to help businesses thrive in the digital realm. Their professionalism, attention to detail, and commitment to delivering outstanding results make them the ideal partner for businesses looking to build a successful online store on the Shopify platform.

This Article was written by

The Digital Hunt - Shopify Development Company

"We are the leading Shopify web development company offering the best Shopify development services like websites and app development,ect."

For More Information

[hirefreelancewebdeveloper]

We explored some of these options in our guide on hiring WordPress developers. API developers can be found on job boards, developer communities, or professional networks like LinkedIn and Reddit For-hire. Specialized freelance platforms offer a wealth of talent.

[bhushan333]

Articles

Ecommerce

Ecommerce has evolved in many ways since its start, and it’s changing the way we live, shop and do business. Let’s dive into the history and the future of ecommerce.

7 Retail Strategies to Overcome a Growth Plateau

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What is Ecommerce?

Ecommerce (or electronic commerce) is the buying and selling of goods (or services) on the internet. It encompasses a wide variety of data, systems, and tools for online buyers and sellers, including mobile shopping and online payment encryption.

Most businesses with an ecommerce presence use an ecommerce store and/or an ecommerce platform to conduct online marketing and sales activities and to oversee logistics and fulfillment.

I'm ready to start building or already have my own ecommerce store.

TRY BIGCOMMERCE

I have questions and would like guidance from an ecommerce expert.

TALK TO SALES

To fully understand ecommerce, let’s take a look at its history, growth and impact on the business world. We will also discuss some advantages and disadvantages to ecommerce, plus predictions for the future.

Types of Ecommerce

Generally, there are six main models of ecommerce that businesses can be categorized into:

B2C.

B2B.

C2C.

C2B.

B2A.

C2A.

Let’s review each type of electronic commerce in a bit more detail.

1. Business-to-Consumer (B2C).

B2C ecommerce encompasses transactions made between a business and a consumer. B2C is one of the most popular sales models in the ecommerce context. For example, when you buy shoes from an online shoe retailer, it’s a business-to-consumer transaction.

2. Business-to-Business (B2B).

Unlike B2C, B2B ecommerce encompasses sales made between businesses, such as a manufacturer and a wholesaler or retailer. B2B is not consumer-facing and happens only between businesses.

Business-to-business sales often focus on raw materials or products that are repackaged before being sold to customers.

3. Consumer-to-Consumer (C2C).

C2C is one of the earliest forms of ecommerce. Customer-to-customer relates to the sale of products or services between customers. This includes C2C selling relationships, such as those seen on eBay or Amazon.

4. Consumer-to-Business (C2B).

C2B reverses the traditional ecommerce model, meaning individual consumers make their products or services available for business buyers.

For example, the iStockPhoto business model in which stock photos are available online for purchase directly from different photographers.

5. Business-to-Administration (B2A).

B2A covers the transactions made between online businesses and administrations. An example would be the products and services related to legal documents, social security, etc.

6. Consumer-to-Administration (C2A).

C2A is similar to B2A, but consumers sell online products or services to an administration. C2A might include online consulting for education, online tax preparation, etc.

B2A and C2A are focused on increased efficiency within the government via the support of information technology.

History of Ecommerce

Ecommerce was introduced about 40 years ago in its earliest form.

Since then, electronic commerce has helped countless businesses grow with the help of new technologies, improvements in internet connectivity, added security with payment gateways, and widespread consumer and business adoption.

Ecommerce Timeline

1969: CompuServe is founded.

Founded by electrical engineering students Dr. John R. Goltz and Jeffrey Wilkins, early CompuServe technology was built utilizing a dial-up connection.

In the 1980s, CompuServe introduced some of the earliest forms of email and internet connectivity to the public and dominated the ecommerce landscape through the mid-1990s.

1979: Michael Aldrich invents electronic shopping.

English inventor Michael Aldrich introduced electronic shopping by connecting a modified TV to a transaction-processing computer via telephone line.

This made it possible for closed information systems to be opened and shared by outside parties for secure data transmission — and the technology became the foundation for modern ecommerce.

1982: Boston Computer Exchange launches.

When Boston Computer Exchange launched, it was the world’s first ecommerce company.

Its primary function was to serve as an online market for people interested in selling their used computers.

1992: Book Stacks Unlimited launches as first online book marketplace.

Charles M. Stack introduced Book Stacks Unlimited as an online bookstore. Originally, the company used the dial-up bulletin board format. However, in 1994 the site switched to the internet and operated from the Books.com domain.

1994: Netscape Navigator launches as a web browser.

Marc Andreessen and Jim Clark co-created Netscape Navigator as a web browsing tool. During the 1990s, Netscape Navigator became the primary web browser on the Windows platform, before the rise of modern giants like Google.

1995: Amazon launch.

Jeff Bezos introduced Amazon primarily as an ecommerce platform for books.

1998: PayPal launches as an ecommerce payment system.

Originally introduced as Confinity by founders Max Levhin, Peter Thiel, Like Nosek and Ken Howery, PayPal made its appearance on the ecommerce stage as a money transfer tool.

By 2000, it would merge with Elon Musk’s online banking company and begin its rise to fame and popularity.

1999: Alibaba launches.

Alibaba Online launched as an online marketplace with more than $25 million in funding. By 2001, the company was profitable. It went on to turn into a major B2B, C2C, and B2C platform that’s widely used today.

2000: Google introduces Google AdWords as an online advertising tool.

Google Adwords was introduced as a way for ecommerce businesses to advertise to people using Google search.

With the help of short-text ad copy and display URLs, online retailers began using the tool in a pay-per-click (PPC) context. PPC advertising efforts are separate from search engine optimization (SEO).

2004: Shopify launches.

After trying to open an online snowboarding equipment shop, Tobias Lütke and Scott Lake launched Shopify. It’s an ecommerce platform for online stores and point-of-sale systems.

2005: Amazon introduces Amazon Prime membership.

Amazon launched Amazon Prime as a way for customers to get free two-day shipping for a flat annual fee.

The membership also came to include other perks like discounted one-day shipping and access to streaming services like Amazon Video and members-only events like “Prime Day.”

This strategic move helped boost customer loyalty and incentivize repeat purchases. Today, free shipping and speed of delivery are the most common requests from online consumers.

2005: Etsy launches.

Etsy launched, allowing crafters and smaller sellers to sell products (including digital products) through an online marketplace. This brought the makers community online — expanding their reach to a 24/7 buying audience.

2009: BigCommerce launches.

Eddie Machaalani and Mitchell Harper co-founded BigCommerce as a 100% bootstrapped ecommerce storefront platform. 

Since 2009, more than $25 billion merchant sales have been processed through the platform, and the company now has headquarters in Austin, San Francisco and Sydney.

2011: Google Wallet introduced as a digital payment method.

Google Walletwas introduced as a peer-to-peer payment service that enabled individuals to send and receive money from a mobile device or desktop computer.

By linking the digital wallet to a debit card or bank account, users can pay for products or services via these devices.

Today, Google Wallet has joined with Android Pay for what is now known as Google Pay.

2011: Facebook rolls out sponsored stories as a form of early advertising.

Facebook’s early advertising opportunities were offered to Business Page owners via sponsored stories. With these paid campaigns, ecommerce businesses could reach specific audiences and get in the news feeds of different target audiences.

2011: Stripe launches.

Stripe is a payment processing company built originally for developers. It was founded by John and Patrick Collison.

2014: Apple Pay introduced as a mobile payment method.

As online shoppers began using their mobile devices more frequently, Apple introduced Apple Pay, which allowed users to pay for products or services with an Apple device.

2014: Jet.com launches.

Jet.com was founded by entrepreneur Marc Lore (who sold his previous company, Diapers.com, to Amazon.com) along with Mike Hanrahan and Nate Faust.

The company competes with Costco and Sam’s Club, catering to folks looking for the lowest possible pricing for longer��shipping times and bulk ordering.

[emmastowe]

A Clear Present and Abstract Future

Hello fellow bloggers, users and readers! My name is Emma Stowe, and I am looking forward to presenting bits and pieces of my professional journey, both through the classroom and work experiences, with those near and far. I am currently a Junior at Central Michigan University, originally from South Lyon, MI, pursuing a degree in Marketing and Logistics. Being the daughter of a business owner, I have always been surrounded by price tags, receipt booklets, invoices and of course, customers. Growing up in this environment helped to shed light on my passion for business. Working and practically living in a business atmosphere, I quickly learned the importance of great communication skills, a strong initiative and internal confidence that must often seeps through.

Throughout my college journey I have been able to expand and enhance this skill set. I’m a proud member of Professional Marketing and Sales fraternity, Pi Sigma Epsilon, which has taught me the proper way to communicate in a strictly professional environment. I have also held two summer internships with ALDI Inc., one of which was following my freshman year of college, which helped me understand the importance of initiative. Finally, on-campus, I have worked my way to becoming President of a student-led organization, Infusion Dance Team. This team has allowed me to continue to pursue an art that I love while remaining a confident, leader in the eyes of team members.

I’ve had recruiters, interviewers and even family members ask me what my career goals are, and I never give a very specific answer. Instead, I supply a more abstract, yet certain response. A career goal of mine is to work with those around me, as well as, external clients, customers or vendors and form unforgettable relationships. Whether I end up in retail, purchasing, account management or human resources, I am certain I will be forming connections, and my goal is to make those connections long lasting. If I had to be more specific, I would love to end up working with beauty or fashion product, possibly in the retail industry. I’ve always held a “look good, feel good” belief, and with the right product, others can begin to experience this philosophy of mine. I have aspirations of becoming a leader or manager in the organization I end up at, and I know with proper communication, initiative and confidence I can obtain this role.

I wish I could say that I decided to start this blog page on my own, but instead I was encouraged by the course, “Social Media and Emerging Technologies in Business” at Central Michigan University. I can honestly say that when I enrolled in this course, I didn’t think opening a tumblr account would be my first assignment, but I’m delighted that it was. With this blog that I hope to continue after this course, I hope to accomplish a better sense of networking with the unknown. I also am looking forward to understanding social media from a business standpoint rather than a personal standpoint. The text, “The Social Organization”, by Anthony Bradley and Mark McDonald, outline a few helpful hints on what it means to be a social organization, as well as, how businesses can become a social organization. According to the text, a social organization is “one that strategically applies mass collaboration to address significant business challenges and opportunities (Bradley & McDonald, 2011, pg. 5). As social media becomes a greater part of our everyday lives, it becomes more important that organizations understand not only the necessity of social media, but also the power and convenience that it holds.

Not every organization has taken the route of a social organization, but instead they have developed only a social media platform; however, in my opinion, Shopify, an E-Commerce and POS system application, created an initiative that mirrored the idea of a social organization. My mother’s business utilizes Shopify POS to keep track of her inventory and transactions which has allowed me to become familiar with the company. From a customer standpoint, Shopify supplies constant improvements for their customers within the application and responds practically immediately to complaints. On the other hand, CEO Tobias Lütke explains in the clip, “Shopify Roadshow”that Shopify allows connectivity between the users and the employees. Employees can reward and view the progress that their fellow co-workers are making which allows for collaboration and the best possible growth for Shopify. This is an organization where “employees, customers, suppliers, and all other stakeholders can participate directly in the creation of value (Bradley & McDonald, 2011, pg. 5). Shopify uses its technology, both publicly and internally, to create a sense of community, purpose and social media. Customers and employees alike can interact with one another at ease to provide solutions and creative initiatives.

There are certainties in the present and general predictions of the future that I can make not only about my career and lifestyle, but also about the trend of social media and technology. There is no doubt that this field will continue to grow because it is clear that organizations who have transformed with technology have become more effective, efficient and collaborative. Like Shopify, organizations must understand that the communication within an organization is just as important, if not more important, than communicating with their customers.

After getting a small dose of what this course will entail, I’m excited to continue to share my thoughts, opinions and stories on a social platform that will benefit how I interact both face-to-face and screen-to-face.

Bradley, Anthony J., and Mark P. McDonald. The Social Organization. Boston, Harvard

Business School Publishing, 2011.

Shopify. (2016, August 8). Shopify Roadshow Documentary. Retrieved from

youtube.com/watch?v=EDleqidmsXA

[michaelcchang3]

Dear 5^{[((Myspace))]}^5 [((÷))] 4ˇ5ˇ((LinkedIn/Facebook/Twitter/Tumblr/Flikr/Pinterest/Instagram/Tinder/Discord/Line/Telegram/WeChat/WhatsApp/Viber/Snapchat/Shopify/Zoom/TikTok))ˇ5ˇ4 (+) ÷ (+) 4^4^(San Diego Reader, Los Angeles Daily News, Seattle Post-Intelligencer, Chicago Sun-Times/ Washington Examiner/ Boston Globe, Atlanta Daily World, Atlanta Journal-Constitution, Tampa Bay Times + ^^ˇˇmessengerˇˇ^^ icon + 1 – 19 e-mail or e-mails w/ wo earphone + phone number or numbers w/ wo ext. numbers Ø, 0, 0^2, 0^3, 0^4, 0^5, 0^6, 0^7, 0^8, 0^9, 0^10, ł, 1, 1^2, 1^3, 1^4, 1^5, 1^6, 1^7, 1^8, 1^9, 1^10, 2, 2^2, 2^3, 2^4, 2^5, 2^6, 3, 3^2, 3^3, 3^4, 4, 4^2, 4^3, 5, 5^2, 6, 6^2, 7, 7^2, 8, 8^2, 9, 9^2, 1 – 9, 2, 3, 4, and 9, 2, 8, 16, 32, and 64, 3, 27, and 81, 4, 16, and 64, 5, and 25, 6, and 36, 7, and 49, 8, and 64, 9, and 81, 1 – 9, 1 – 99)^4^4 (+) ÷ (+) 4ˇ5ˇ((LinkedIn/Facebook/Twitter/Tumblr/Flikr/Pinterest/Instagram/Tinder/Discord/Line/Telegram/WeChat/WhatsApp/Viber/Snapchat/Shopify/Zoom/TikTok))ˇ5ˇ4 [((÷))] 5^{[((Myspace))]}^5:

Individuals between the ages of eighteen and thirty-four, I would like to REINTRODUCE, NOT INTRODUCE, YOU A BEGINNER’S, INTERMEDIATE’S, AND PROFESSIONAL’S GUIDE TO DISTRIBUTION SCORES, FICO SCORES, AND AVERAGE SCORES; SEE INTO THE BELOW OUTLINE SHOWCASING THE DEMONSTRATION OF THE THREE FULL SCORES, DISTRIBUTION, FICO, AND AVERAGE ALL IN ONE; AS YOU PROCEED, NOTICE THAT THE LARGEST SUM, 10,000, IS WORTH A PERCENTMILL; WHATEVER LEFTOVER PERCENTMILLS I HAVE GOT, I AM GOING TO BE REVISITING MY MORTGAGE TUTORAGE ANY DAY TO FINISH IT UP; NOTICE THAT, AS I REACH THE MODERATE SUM, 1,000, THE SUM IMMEDIATELY SPELLS NOT ONLY SALES TAX AND TAX RETURNS BUT ALSO CONSUMER’S RATES AND TAXPAYER’S RATES. AS YOU CARRY INTO THE FOURTH WEEK OF AUGUST 2022, YOU SHOULD BE GOOD TO GO AS YOUR PREDECEASING HIGH SCHOOL YEARS RESUME THE SUCCESSIVE SCHOOL YEARS; I WELCOME YOU INTO THE ENVIRONMENTAL POLITICS; EITHER THAT, OR ENJOY YOURSELVES. AS I PROCEED FROM HEREON AND HEREAFTER, UNDERSTAND THIS: WHILE IT IS TRUE I HAVE A PRIOR HISTORY OF NON-BINARY DEVELOPMENT, THROUGH RECENT REFLECTION UPON MY PAST LIFE, I HAVE FINALLY ARRIVED AT THE STRUCTURAL DEVELOPMENT THAT HAS ALWAYS SUIT ME WELL: DISJOINTED TERNARY FORM; NO MORE OF THE MISALIGNMENT.For application material, dial 1; for application history, dial 2; for application submission, dial 3; for the waitlist, dial 4; for application confirmation, dial 5; for final application results, dial 6. To obtain online journals w/ wo social media, dial 7; to obtain online journals w/ social media completely, dial 8; to obtain physical copies lasting up to 1M copies, stay on the line and hold true to ext. 8. For sales representation w/ wo social media, dial 9. For recreational purposes, dial 2; for educational purposes, dial 3; for professional purposes, dial 4; for administrative purposes, dial 9. For mass marketing and mass communications purposes, dial 2; for telemarketing and telecommunications purposes, dial 8. I WELCOME YOU TO RESPOND THROUGH MY TEN E-MAILS, ONLINE CHAT, AND EARPHONE W/ TEXT MESSAGE, EIGHTEEN SOCIAL MEDIA METHODS, YES “COMMENT” ICON, YES “SHARE” ICON, YES “MESSENGER” ICON, YES TIKTOK, YES M.P. BOX/ P.O. BOX, YES PHONE CALLS, NO SMOKING, PHYSICALLY OR ELECTRONICALLY. IF YOU NEED TO SOBER UP THE ELECTRONIC CIGARETTE, PLEASE ACCESS THE “MESSENGER” ICON, EXHALE THROUGH THE ICON, AND EMPTY THE ICON. 1-(408) 533-5577, 2-(408) 533-5577, 3-(408) 533-5577, 4-(408) 533-5577, 5-(408) 533-5577, 6-(408) 533-5577, 7-(408) 533-5577, 8-(408) 533-5577, 9-(408) 533-5577, 2-(408) 533-5577, 3-(408) 533-5577, 4-(408) 533-5577, 9-(408) 533-5577, 2-(408) 533-5577, 8-(408) 533-5577. TO ACCESS THE KEYBOARD, PLEASE ACCESS YOUR DESKTOP, LAPTOP, OR EVERY OTHER TELEPROMPTER SUCCESSOR. TO HINDER AN INDOOR GENERATION WITH THE ATTACHABLE OR DETACHABLE USB CABLE, DIAL 9. 1-(408) 533-5577, 2-(408) 533-5577, 3-(408) 533-5577, 4-(408) 533-5577, 5-(408) 533-5577, 6-(408) 533-5577, 7-(408) 533-5577, 8-(408) 533-5577, 9-(408) 533-5577, Ø. THE TWENTY-SEVEN EXT. NUMBERS, NINE ADDITIONAL EXT. NUMBERS, AND SIXTEEN REMAINING VACANCIES HAVE BEEN FILLED, 0, 0^2, 0^3, AND Ø, 2, 3, 4, AND 9, 2, AND 8, 1 – 9. THE EIGHTY-ONE TO NINETY-NINE EXTENSION NUMBERS HAVE REACHED THEIR OVEREXCEEDING LIMIT AND THE EXCEEDING AMOUNT OF SOCIAL MEDIA MODALITIES, AND THE EIGHTEEN SOCIAL MEDIA MODALITIES EXCEED INTO NINETEEN TO DEDUCT 1 DEGREE FROM 361 DEGREES. THANK YOU:

I’m Michael Chang, and I proudly sponsor your local, national, and international news/ I’m an exp.-media user, and I customize my own service; I’m a social administrations and facilitations user, and I personalize my own service. Partial synchronization is my preferable correspondence method, and feel free to get back to me via BOTH e-mail AND social media. To hinder an indoor generation, dial 1; to hinder 24/7 indoor exposure, dial 2. The cubic value of ext. number 2 has been deducted; the cubic value of ext. number 2 has been filled. Thank you! (1:05 AM EST, Sunday, August 21, 2022)

1)

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0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1000

= 1000

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= 1100

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= 1200

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= 1300

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= 1400

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-750

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1500

= 1500

7)

Distribution Score:

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

Fico Score:

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1600

= 1600

8)

Distribution Score:

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

Fico Score:

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1700

= 1700

9)

Distribution Score:

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

Fico Score:

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1800

= 1800

10)

Distribution Score:

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

Fico Score:

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 1900

= 1900

11)

Distribution Score:

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

Fico Score:

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2000

= 2000

12)

Distribution Score:

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

Fico Score:

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2100

= 2100

13)

Distribution Score:

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

Fico Score:

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2200

= 2200

14)

Distribution Score:

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

Fico Score:

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2300

= 2300

15)

Distribution Score:

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

Fico Score:

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2400

= 2400

16)

Distribution Score:

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

Fico Score:

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2500

= 2500

17)

Distribution Score:

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

Fico Score:

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2600

= 2600

18)

Distribution Score:

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

Fico Score:

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2700

= 2700

19)

Distribution Score:

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

Fico Score:

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2800

= 2800

20)

Distribution Score:

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

Fico Score:

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 2900

= 2900

21)

Distribution Score:

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

Fico Score:

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3000

= 3000

22)

Distribution Score:

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

Fico Score:

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3100

= 3100

23)

Distribution Score:

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

Fico Score:

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3200

= 3200

24)

Distribution Score:

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

Fico Score:

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3300

= 3300

25)

Distribution Score:

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

Fico Score:

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3400

= 3400

26)

Distribution Score:

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

Fico Score:

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3500

= 3500

27)

Distribution Score:

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

Fico Score:

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3600

= 3600

28)

Distribution Score:

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

Fico Score:

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3700

= 3700

29)

Distribution Score:

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

Fico Score:

1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3800

= 3800

30)

Distribution Score:

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

Fico Score:

1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 3900

= 3900

31)

Distribution Score:

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

Fico Score:

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4000

= 4000

32)

Distribution Score:

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

Fico Score:

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4100

= 4100

33)

Distribution Score:

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

Fico Score:

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4200

= 4200

34)

Distribution Score:

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

Fico Score:

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4300

= 4300

35)

Distribution Score:

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

Fico Score:

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4400

= 4400

36)

Distribution Score:

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

Fico Score:

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4500

= 4500

37)

Distribution Score:

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

Fico Score:

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4600

= 4600

38)

Distribution Score:

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

Fico Score:

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4700

= 4700

39)

Distribution Score:

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

Fico Score:

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4800

= 4800

40)

Distribution Score:

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

Fico Score:

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 4900

= 4900

41)

Distribution Score:

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

Fico Score:

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5000

= 5000

41a)

5000 ÷ 50

100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 + 100 (Sales Tax + Tax Returns)

5000 ÷ 100

50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 + 50 (Consumer’s Rates + Taxpayer’s Rates)

100 (50) – 50 (100)

100 (50) – 50 (50) 2

100 – 50 (2)

100 – 100

0 ÷ 10 yrs.

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

10,000 ÷ 10 yrs.

= 1,000

42)

Distribution Score:

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

Fico Score:

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5100

= 5100

43)

Distribution Score:

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

Fico Score:

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5200

= 5200

44)

Distribution Score:

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

Fico Score:

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5300

= 5300

45)

Distribution Score:

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

Fico Score:

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5400

= 5400

46)

Distribution Score:

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

Fico Score:

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5500

= 5500

47)

Distribution Score:

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

Fico Score:

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5600

= 5600

48)

Distribution Score:

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

Fico Score:

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5700

= 5700

49)

Distribution Score:

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

Fico Score:

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5800

= 5800

50)

Distribution Score:

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

Fico Score:

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 5900

= 5900

51)

Distribution Score:

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

Fico Score:

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6000

= 6000

52)

Distribution Score:

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

Fico Score:

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6100

= 6100

53)

Distribution Score:

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

Fico Score:

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6200

= 6200

54)

Distribution Score:

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

Fico Score:

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6300

= 6300

55)

Distribution Score:

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

Fico Score:

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6400

= 6400

56)

Distribution Score:

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

Fico Score:

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6500

= 6500

57)

Distribution Score:

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

Fico Score:

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6600

= 6600

58)

Distribution Score:

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

Fico Score:

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6700

= 6700

59)

Distribution Score:

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

Fico Score:

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6800

= 6800

60)

Distribution Score:

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

Fico Score:

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 6900

= 6900

61)

Distribution Score:

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

Fico Score:

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7000

= 7000

62)

Distribution Score:

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

Fico Score:

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7100

= 7100

63)

Distribution Score:

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

Fico Score:

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7200

= 7200

64)

Distribution Score:

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

Fico Score:

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7300

= 7300

65)

Distribution Score:

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

Fico Score:

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7400

= 7400

66)

Distribution Score:

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

Fico Score:

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7500

= 7500

67)

Distribution Score:

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

Fico Score:

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7600

= 7600

68)

Distribution Score:

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

Fico Score:

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7700

= 7700

69)

Distribution Score:

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

Fico Score:

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7800

= 7800

70)

Distribution Score:

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

Fico Score:

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 7900

= 7900

71)

Distribution Score:

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

Fico Score:

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8000

= 8000

72)

Distribution Score:

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

Fico Score:

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8100

= 8100

73)

Distribution Score:

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

Fico Score:

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8200

= 8200

74)

Distribution Score:

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

Fico Score:

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8300

= 8300

75)

Distribution Score:

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

Fico Score:

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8400

= 8400

76)

Distribution Score:

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

Fico Score:

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8500

= 8500

77)

Distribution Score:

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

Fico Score:

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8600

= 8600

78)

Distribution Score:

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

Fico Score:

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8700

= 8700

79)

Distribution Score:

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

Fico Score:

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8800

= 8800

80)

Distribution Score:

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

Fico Score:

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 8900

= 8900

81)

Distribution Score:

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

Fico Score:

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9000

= 9000

82)

Distribution Score:

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

Fico Score:

4550

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

-4550

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9100

= 9100

83)

Distribution Score:

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

Fico Score:

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9200

= 9200

84)

Distribution Score:

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

Fico Score:

4650

4550

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

-4550

-4650

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9300

= 9300

85)

Distribution Score:

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

Fico Score:

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9400

= 9400

86)

Distribution Score:

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

Fico Score:

4750

4650

4550

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

-4550

-4650

-4750

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9500

= 9500

87)

Distribution Score:

9600

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

-9600

Fico Score:

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9600

= 9600

88)

Distribution Score:

9700

9600

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

-9600

-9700

Fico Score:

4850

4750

4650

4550

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

-4550

-4650

-4750

-4850

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9700

= 9700

89)

Distribution Score:

9800

9700

9600

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

-9600

-9700

-9800

Fico Score:

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9800

= 9800

90)

Distribution Score:

9900

9800

9700

9600

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

-9600

-9700

-9800

-9900

Fico Score:

4950

4850

4750

4650

4550

4450

4350

4250

4150

4050

3950

3850

3750

3650

3550

3450

3350

3250

3150

3050

2950

2850

2750

2650

2550

2450

2350

2250

2150

2050 1950

1850

1750

1650

1550

1450

1350

1250

1150

1050

950

850

750

650

550

450

350

250

150

0-150 -250

-350

-450

-550

-650

-750

-850

-950

-1050

-1150

-1250

-1350

-1450

-1550

-1650

-1750

-1850

-1950

-2050

-2150

-2250

-2350

-2450

-2550

-2650

-2750

-2850

-2950

-3050

-3150

-3250

-3350

-3450

-3550

-3650

-3750

-3850

-3950

-4050

-4150

-4250

-4350

-4450

-4550

-4650

-4750

-4850

-4950

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 9900

= 9900

91)

Distribution Score:

10000

9900

9800

9700

9600

9500

9400

9300

9200

9100

9000

8900

8800

8700

8600

8500

8400

8300

8200

8100

8000

7900

7800

7700

7600

7500

7400

7300

7200

7100

7000

6900

6800

6700

6600

6500

6400

6300

6200

6100

6000

5900

5800

5700

5600

5500

5400

5300

5200

5100

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000

1900

1800

1700

1600

1500

1400

1300

1200

1100 1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

-5100

-5200

-5300

-5400

-5500

-5600

-5700

-5800

-5900

-6000

-6100

-6200

-6300

-6400

-6500

-6600

-6700

-6800

-6900

-7000

-7100

-7200

-7300

-7400

-7500

-7600

-7700

-7800

-7900

-8000

-8100

-8200

-8300

-8400

-8500

-8600

-8700

-8800

-8900

-9000

-9100

-9200

-9300

-9400

-9500

-9600

-9700

-9800

-9900

-10000

Fico Score:

5000

4900

4800

4700

4600

4500

4400

4300

4200

4100

4000

3900

3800

3700

3600

3500

3400

3300

3200

3100

3000

2900

2800

2700

2600

2500

2400

2300

2200

2100

2000 1900

1800

1700

1600

1500

1400

1300

1200

1100

1000

900

800

700

600

500

400

300

200

100

0-100 -200

-300

-400

-500

-600

-700

-800

-900

-1000

-1100

-1200

-1300

-1400

-1500

-1600

-1700

-1800

-1900

-2000

-2100

-2200

-2300

-2400

-2500

-2600

-2700

-2800

-2900

-3000

-3100

-3200

-3300

-3400

-3500

-3600

-3700

-3800

-3900

-4000

-4100

-4200

-4300

-4400

-4500

-4600

-4700

-4800

-4900

-5000

Average Score:

0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0 + 0

0 + 10000

= 10000

Copyright Statement:

I hereby consent that, under copyright law, I give permission for my article to be redistributed to the public either one-dimensionally, optically, electronically, tolerably, physically, neutrally, environmentally, anti-sustainably, or backwardly and either progressively, pro-sustainably, multi-dimensionally, sociably, manually, minimally, diminutively, deoptically, or accessibly. Under copyright law, I give permission for my name to be distributed under the article I would be releasing to the public, as I would not be held solely responsible for any opinions that have been expressed with regards to my article.

Born in 1993, Michael Chang is a political journalist of Los Angeles Times, Chicago Tribune, and New York Times and has stricken up his journal career directly from social media off of the keyboard as opposed to writing utensils and has sought out the best quality journal career in his seeking out the news reports. He has come to conceive his journal career off of his own social media method, Facebook, and would be holding true to Facebook journalism for the sociably and manually accessible. Social media journalism is the exact career he has been seeking out and has been holding true to a history of mock journals delivered to the news reports and has been setting aside all live blogging in embrace of journalism for the sociably and manually accessible. In embrace of the innovative journalism method, Michael Chang encourages the usage of the method more so often with the repeated minimization, not elimination, to writing utensils, for the keyboard remains widely accessible as to the minimization. He is one of the premiere social media journalists in substitution of live blogging and would always be able to reconsider live blogging through repeated restoration to personal contact during times when he is not publishing. During times when he is not publishing, he would be setting aside all literary technique he has ever applied to his social media journalism and has come to widely favor a number of technique. The number of technique have to include flashback, foreshadowing, idioms, imagery, metaphors and similes in particular and has come to disfavor hyperbole and would always be minimizing the hyperbole, not unless he were to strike them up for entertainment purposes. For entertainment purposes, he would either hold true to minimal hyperbole or hold true to maximal literary technique for educational purposes, and, for educational purposes, he would be covering a variety of topics in accordance to his history of mock journals. With regards and with disregard to his journal career, his preferable technology distributor is Apple as his preferable internet provider is AT&T, and, as an Apple and AT&T accessor, the technology distributor and internet provider remain true to his everyday exposure to water and electricity in place of penmanship and writing utensils, both of which he would continue to access along with Verizon and Twitter as to the environmental sustainability. As to the sustainability, he prefers holding true to the water and electricity in his everyday life with online video browsing with access to minimal amounts of physical videos through fully utilizing YouTube. The progressivism he has come to absorb is extracted from solitary progressive education, and solitary progressive education is his preferable mode of Communications and Journalism, having specialized in that area of expertise directly from Carnegie Mellon University and having specialized in the Anglican-Anglophone alternation between multinational English-speaking countries. As an English-language journalist, he is a frequent accessor of Google translations, as the translations have proven to be the exact digital device in the multilingual journalism at his dispense and is bound to hold true to English-language journalism under the digital device of six online translators. A philanthropist, Michael Chang is widely supportive of traditional, ternary developmental, Minimalistic, and innovative education and encourages the usage of social media amongst the innovative more so often and encourages that usage to be put into practice amongst liberal economics as well, his preferable method of economics when compared to most positions. A Christian believer, Michael Chang makes occasional appearances in PFLAG, an LGBT related organization, and proudly supports multiple sexualities every once in a while; he is a fan of Ellen DeGeneres.

Also a clarinetist, pianist, voice actor, and music technician, Michael Chang encourages the usage of lumber related musical instruments and touchless modes of music technology more so often. As a frequent accessor of lumber related musical instruments and touchless music technology, Michael Chang encourages Apple Music to be put into full use in the everyday lives of both Apple users and non-users alike. With the usage of the touchless mode of music technology, Michael Chang encourages the alternation between minimal, maximal, and maximal-tolerable analogue, digital, and livestream recordings and encourages the usage of the livestream more so often, both traditionally and innovatively. He encourages the usage of not only lumber related musical instruments and touchless music technology but also every other digital access to musical instruments and music technology in succession and precession to the lumber related and touchless both traditionally and innovatively. Michael Chang is a frequent customer of Woodwind and Brasswind and is a Yamaha user in the keyboard specialty. As a Yamaha user, he personably obliges himself to take up matching descriptions as to the distribution of his musical instruments. When not practicing or performing, he would often be dedicating his time to political journalism and philanthropy of moderate esteem, and, as a Communications and Journalism specialist of his own, his specialty in Communications and Journalism and Commercialization of the Autonomous had begun as a singular pair of qualities that eventually began to double its own value. That doubling that lead him towards the Commercialization of the Autonomous is the exact determining factor of encouraging the usage of lumber related products and touchless modalities of technology in general. He encourages the usage of lumber minority and touchless technology majority to the brink of repeated diminution and augmentation to the minority and majority counterparts. As a music technician, he encourages all lumber minority and touchless technology majority to hold true to their conceptions, and those conceptions are a purely handmade quality and quantity in a repeated exchangeability amongst each other. Michael Chang encourages the usage of preconceived lumber related products in general and encourages elderly wood stock to be revived through the most touchless modes of technology. As to the music technology, he encourages the repeated usage of digital recordings in physical format or convert directly to livestream as well as he encourages the repeated minimization to analogue recordings of and before the generation of the LP and LPM. His preferable format of recording is the CD as his preferable method of surround sound is 24-HD. He is opposed to electronic music not because of deference but because he encourages human interaction amongst variable artists with access to lumber related musical instruments and touchless modes of music technology to the brink of repeated authenticity. He seeks out authentication to the most frequently accessed choices of lumber related musical instruments and opposes artificialization to musical instruments. His opposition to artificialization of musical instruments is his modality of music advocacy. His music advocacy modality is the exact methodology he continues to rely on and would always rely on in his everyday access to lumber minority and touchless majority. He is a Buffet Crampon/ Yamaha Artist.

As a music technician, Michael Chang encourages the usage of Spotify more so often, as Spotify is the sole method of radio connection without portable qualities in alternation with YouTube or singularization from YouTube. Michael Chang encourages the touchless radio to be put into full use more so often, as the touchless radio is the exact modality of receiving transmissions without the microphone; without the microphone, the transmissions remain actively resonant without consuming radiology. Without consuming radiology, the radiation-free device continues to be fully accessed off of individual devices; Michael Chang encourages that radiation-free device to continue to be fully accessed without consuming radiology and without the additional microphone. As a music technician, Michael Chang encourages the usage of Spotify as the sole method of substitution to the microphone, and the substitute is the exact adjustable and adaptable radio connection with the reliable inserted microbes. With the reliable inserted microbes, he encourages the usage of Spotify as not any mere sole method of radio connection but also connectable and encourages the connectable to be fully accessed off of the hybrid or electric vehicle and every other vehicle of the exact same generation, albeit CD players. He encourages the usage of Spotify either on its own or rotationally with Apple Music and encourages the rotation to take shape more so often. He encourages the invention of double radio connection conceived off of the rotation between Apple Music and Spotify to the brink of optical radio connection and encourages optical radio connection to apply to predeceasing generations of motor vehicles. He encourages carbon-neutral emission amongst predeceasing generations of motor vehicles to the brink of retaining the CD player. Michael Chang encourages the repeated singularization and collection of Apple Music and Spotify as to the singularization and collection of multiple generations of motor vehicles through valid CD players and touchless radios with or without additional handmade transmissions. He encourages analogue recordings of and before the generation of the LP and LPM to hold true to their vintage qualities as to the vintage vehicle and encourages livestream to be fully accessed amongst vintage vehicle consumers and encourages gas emission consumers to remain true to livestream other than analogue recordings. He encourages the alternation between multiple generations of motor vehicles and of audio recordings ranging from gas emission to carbon-neutral emission and ranging from massively proportional to touchless as to the audio recordings as well as rotational between the hybrid and electric and rotational between Apple Music and Spotify. He is a fan of Toyota; he is a Diplomatic Artist.

A social media savvy, Michael Chang has a prior history of encouraging water and electricity provision and discouraging addiction to and from the social media platform and encourages the repeated provision to be covered by all social media savvies and discourages addiction to the brink of enhanced rationality on a daily basis. He encourages social media journalism to be picked up on more so often, as social media journalism serves as an alternate form to online journalism, which serves as an alternative form to handwritten journalism. He encourages the usage of every other periodic element of or related to oil, meth, or paper, as the three periodic elements are known for their repeated extraction of handwritten journalism. In the repeated battling with social media addiction and disciplinary action involving water and electricity provision, he encourages periodic element immersion to take the place of online immersion, as periodic element immersion surpasses 1980s culture, and that surpass immediately creates social media savviness. He encourages accessibility to ternary transmissions through accessibility to three water and electricity providers and encourages accessibility to three water and electricity providers to surpass their time span. He is an occasional accessor of T-Mobile and holds true to that occasion in his everyday life as he holds true to his faithfulness and loyalty to Twitter as his third water and electricity provider and encourages ternary transmissions to take the place of carbon-neutral emissions. In substitution of carbon-neutral emissions, he encourages carbon-neutral emissions to triple amongst themselves or de-neutralize amongst each other as to the alternating gas emission and electric transmissions. Michael Chang encourages carbon-neutral tripling to take the place of multi-destination transportation and multi-transmissive indoor activities, coal mining, and pricing. He encourages periodic element immersion of and beyond the social media generation to double the value of online immersion of and beyond the 1980s, as that doubling immediately transports ext. numbers 1 – 9 beyond their time in equivalence to the amount of periodic elements. In equivalence to the amount of periodic elements, he encourages repeated alternation between online immersion of and beyond the 1980s and periodic element immersion of and beyond the social media generation through combination and separation as well as individualization and collection. He encourages the repeated individualization and collection of online immersion of and beyond the 1980s and periodic element immersion of and beyond the social media generation as to the repeated combination and separation of the contrasting qualities and quantity auto-generators. In alternate form to all of online video browsing and online music channels, he encourages online video browsing and online music channels to be combined with online journalism more so often. He encourages disjointed ternary form as to the handwritten journalism, online journalism, and social media journalism, physical videos, online video browsing, and social media screening, and physical audio recordings, online music channels, and livestream. His handwriting is cursive.

An anthropologist, Michael Chang has associated himself with up to and no more than eighteen news reports and has come to stay in the now directly from an increasing rivalry with the San Francisco Chronicle and San Francisco Examiner, both of whom he has come to dissociate his journalism from. In an increasing alliance with eighteen news reports, Michael Chang continues to hold true to his full-time career and seeks out the best exchangeability with the performing arts. Through exchangeability, Michael Chang expects and expectates an equivalent amount of time in the dedication to the literary arts and performing arts. In the dedication to the literary arts and performing arts, Michael Chang gives priority to the stamina more than the aroma as well as he gives priority to intellect over beauty; given his male gender, he associates his image with handsomeness every once in a while and would only give priority to handsomeness on occasion. Given his male gender, Michael Chang the anthropologist expects and expectates the best results out of both genders in the stamina as opposed to aroma. A frequent customer of nearby retailers, Michael Chang demands and extracts the best results out of clothing as a daily necessity, and, as a daily necessity, aroma is second-in-command for the anthropologist. Michael Chang expects to extract greater hygiene than aroma and gives full balance to oil prices and coal prices as opposed to greater priority to oil prices. He encourages greater priority to coal prices more so often in the regained stamina. He recommends the San Francisco Chronicle and San Francisco Examiner to high school journalism and part-time journalism as a setup for full-time journalism. As a setup for full-time journalism, Michael Chang is an advocate for environmental politics and encourages the adolescence to be associated with environmental politics more so often; he encourages the adolescence to stay well informed as to their succeeding generations, and each succeeding generation of well informed politics for the age range stays true to its environmentalism. He encourages water and electricity, elasticity, and elasticity and electricity provision in adolescence as a setup for affordable housing later in life; he encourages the three selective elements to hold true to their selective process amongst all ages. Through free selection, Michael Chang encourages increasing modernization to Science, Technology, Engineering, and Math (STEM). As a Christian believer, Michael Chang does not hesitate to adapt and adjust to the STEM in embrace of the concreteness that lies within the STEM as opposed to his belief system and encourages seeking out individually selective ecosystems. He is a vegetarian and vegan on the weekends and stays free of meat eating throughout each weekend; he encourages the dining pattern amongst the religiously and irreligiously associated and dissociated; he is absorbent and dissolving of atheism and encourages the dining pattern amongst the religiously associated more so often. A 1990s consumer, Michael Chang associates himself with the feature films of and beyond his generation of partially and completely restricted interest, most notably Mel Gibson’s “Braveheart,” Ken Kavanaugh’s “Hamlet,” James Cameron’s “Titanic,” and Peter Jackson’s “Lord of the Rings Trilogy,” all of which have invited comparison and contrast to each other within the timespan of 1990s consumer’s rates; the trilogy has served as his incubator, and that incubator lead directly to anti-Harry Potter franchise.

When not committing to the performing arts or to the Communications and Journalism and Commercialization of the Autonomous, Michael Chang enjoys his civil life within the autonomies on his own time. While it is true he seeks out moderate esteem within the Communications and Journalism and Commercialization of the Autonomous, he remains contempt as to the quality descriptions he could possibly conceive, and his quantity descriptions fully depend on the time he has spent in the performing arts. He is an enthusiast of the Amazon and eBay retail websites and encourages digital shopping in place of online shopping more so often, with the reliable social media platform to fully access the retail websites and encourages the usage of the platform amongst innovative online browsers. As he seeks out the best quality and quantity handmade products, he is a familiar face in the Obsessive Compulsive Disorder (OCD) and assists with fighting OCD in everyday life with the accessibility to quality and quantity handmade products. As to the accessibility, he encourages the increasing and decreasing usage of lithium, and the rising and falling lithium prices is his methodology of OCD advocacy and encourages the usage of individual keyboards in place of writing utensils of or related to oil prices or meth prices. He encourages enhanced rationality to be put into practice in everyday life in order to fight OCD, and, in order to fight OCD, he encourages OCD to be pacified through the repeated minimization to handmade products through repeated alternation with touchless technology. He encourages nicotine prices to be put into full use in a repeated dissociation from tobacco products and discourages the usage of tobacco through every other nicotine prices and encourages fighting Chronic Obstructive Pulmonary Disease (COPD) through repeatedly falling coal prices, as falling coal prices are COPD prevention and preventatives. A medical enthusiast, he may be no medical expert but maintains health related journals as to the knowledge he has the intent of expressing. He is a familiar face in the Medical Library Association (MLA) and has come to partially dissociate himself from the MLA. He is a mortgage tutor in his private life and has sought out local tutoring directly from nearby residents and welcomes social media users to see into his tertiary Facebook account, “Michael Chang’s Mortgage Tutorage for the Previous and Successive Age of 18”. He welcomes social media users to see into his secondary Facebook account, “The Clarinet Studio of Michael Chang,” to see into his musically related knowledge and see into his remaining fifteen social media modalities. Michael Chang lives in Long Beach, CA, USA and is hoping to become a married man without children and is planning to marry; he is legitimate.

To know more about him, please TRIPLE AURAL at (408) 533-5577 OR TRIPLE WRITTEN; e-mail mcc0814@icloud.com, michaelc0814@gmail.com, 08141993michaelc@gmail.com, michaelcchang3@gmail.com, michaelcchang3@yahoo.com, michaelc0814@outlook.com, michaelcchang3@outlook.com, michaelc0814@hotmail.com, or michaelcchang3@hotmail.com. To reach out to Michael Chang in variable transmissions, please write to him at his REMAINING E-MAILS, his auxiliary and notary: michaelcchang3@aol.com, michaelc0814@aol.com, and michaelc08141993@yahoo.com.

For recreational purposes, please write to him at mcc0814@yahoo.com, michaelc08141993@outlook.com, mcc0814@hotmail.com, michaelc08141993@aol.com, michaelc0814@icloud.com, and michaelc08141993@icloud.com. To dial in the recreational hotline, please reach out to him with ext. numbers 1 – 9 ON REPEAT; Michael Chang holds true to his Apple support and support of every other technology distributor and resolver.

Faculty (rev. 3 (FINALIZED) (TBD*)):

Born in 1958, Ellen DeGeneres is a former television personality and comedian and is guest adjunct faculty at Carnegie Mellon University. As guest adjunct faculty, she specializes in the Arts Management and Entertainment Industry Management and is able to mentor the area of political journalism in particular, as the invalidation to opinions is a specialty within her possession. As a specialty within her possession, Ellen DeGeneres has a prior history of repeated invalidation to opinions based on political journalism and has held true to that invalidation throughout her involvement with television work, and, throughout her involvement with television work, she has had a prior history of alternation between radio communications as well as mass communications and telecommunications, and the aural and written communications she has gotten used to has lead directly to repeated specialty in the political journalism, both aurally and compositely. As guest adjunct faculty of Carnegie Mellon University, she is solely emphasized on the Los Angeles campus and is partially dissociated from all of the University and would always be mentoring on the Los Angeles campus, her sole emphasis. With the artistic and entertaining qualities she is able to mentor, her mentorship involves repeated absorbance and dissolution to her satirical humor, as satirical humor is the exact genre she has come to regard as completely personal and not personable. While it is true her personable qualities are dismissive and absorbent of her satirical humor, every other genre of a total separation from satirical humor is the exact artistic and entertaining qualities she has always had, and that total separation was the exact determining factor of having been able to hold true to her television personality. That determining factor was the exact quality that lead directly to revealing not her homosexuality but every other quality in a total dismissal to her homosexuality. One of the greatest living philanthropists, Ellen DeGeneres has held true to her television personality ever since her rise to fame and has held true to her investments through the best quantity money management she has got, and the quantities she has held true to have lead directly to her financial success in all of Arts Management and Entertainment Industry Management. While it is true she has set aside all personal success to garner personable success, her personable success was the only way to see into the world of commerce, and that commerce is the exact teaching philosophy she has come to present within the Arts Management and Entertainment Industry Management. An environmentalist, Ellen DeGeneres has garnered the best results from paper reduction and energy consumption. An atheist, Ellen DeGeneres does not hesitate to partially associate herself with religious freedom, and this is especially true of Christianity.

An animal activist, Ellen DeGeneres is a master of separatist behavior whose familiarity with animal activism lead directly to repeated separatist behavior in her everyday life, in contrasting nature to behavioral therapy. In contrasting nature to behavioral therapy, she specializes in the repeated separatist behavior between the animal kingdom and human species, as the occupational therapy may be embedded within her heritage, but she has come to favor separatism over occupancy. As an advocate for carbon-neutral emission, she embraces the emissive in her everyday life to the brink of repeated decentralization to all gas emissions and electric transmissions and prefers holding true to the carbon-neutral tripling. As to the carbon-neutral tripling, she continues to seek out alternatives and alternates to the occupational therapy and encourages wholesomeness directly from those alternatives and alternates. She encourages wholesomeness to be fully extracted in everyday life whether originally, alternatively, or alternately as to the occupational therapy and has a long lasting legacy of holding true to the alternatives and alternates herself. A medical enthusiast with no expertise, Ellen DeGeneres has come to value CVS Health of and beyond the industrial age and continues to fully consume electric transmissions in the accessibility to CVS Health. A vegetarian, Ellen DeGeneres is a strong advocate for carbon emission reduction and is structurally Adventist in her appetite; whether daily or weekly, she is able to hold true to vegetarianism once a week with the religiously related structure. With the religiously related structure, she holds true to her atheism.

Biography (rev. 3 (FINALIZED) (*)):

Born in 1999 and raised in Pittsburgh, Pennsylvania, USA, Juliet Evancho, formerly Jacob Evancho, is an Assoc. Prof. of Economics in the flagship institution of education of her hometown, University of Pennsylvania, and that flagship institution of education is the exact destination where out-of-state and out-of-country students and faculty have come to know more than every other destination. As an Assoc. Prof. of Economics, she has divided her teaching career with a modeling career and retailing career, and the alternation between her divisions have lead directly to not only engineering in general but also vehicular engineering, as the study of oil prices has proven to be of and beyond her generation, and the repeated rising of oil prices is the exact motorcade that has been picked up by successive semesters of and beyond the 2020-2021 school year. The repeated rising to oil prices is to the repeated dropping of coal prices, and the rising and dropping of oil and coal prices is exactly what leads directly to the neutralization and de-neutralization of lithium and every other element, and the repeated references to the table of elements is the sole method of determining the neutralization and de-neutralization. It is because of that that the repeated emphasis on the table of elements is the only way to fully determine what would become of oil prices, as the table of succession begins with oil prices and would always lead directly to whichever end. The Economics professor’s native hometown is known to all of the U.S. and the global heritage as a member of the Tri-Valley, where coal prices are repeatedly dropping to the brink of rising oil prices. The flagship institution of education of her hometown is proportionally larger than every other Tri-Valley institution of education. When not teaching, the Economics professor enjoys holding true to modeling and retailing. She is of the Second School of Economics and is emphasized on mortgage calculations more than trigonometry; that emphasis has lead directly to the Graduate Record Examinations (GRE) of many of her students, who have come to scatter themselves across innumerable educational institutions of or related to the GRE. The Economics professor strongly encourages the usage of Apple or Microsoft calculators in everyday life when compared to handheld calculators. She is of the main campus and San Francisco campus of her flagship institution of education and has come to alternate between her native Pennsylvania and California. She is transsexual and holds true to the coeducational School for the Ternary Developer and Progressive Developer, which often serves as a backup to her teaching career in the Second School of Economics. Juliet Evancho was a Johns Hopkins University gender reassignment surgery pursuing individual in pursuit of one of the leading gender reassignment higher institutions of education*. She is a proud supporter of her internationally-renown sister, Jackie Evancho, in the performing arts.

A Pittsburgh Times reader, Juliet Evancho is often associated with her local news report and has sought out national and international news directly from her decentral news reports, Chicago Tribune and New York Times. She widely prefers news reports of or related to the Pittsburgh Times and is associated with her local news report to the brink of dissociation from the Los Angeles Times. With the repeated dissociation from the Los Angeles Times, she widely prefers central and eastern news reports and has sought out the best quality descriptions from central and eastern news reports and has held true to the main campus of University of Pennsylvania more than the Los Angeles campus. As a central and eastern news report reader, she continues to associate herself with the central and eastern set time and has held true to her teaching career in the pacific set time far less than her teaching career in the eastern set time. Juliet Evancho holds true to not only the Second School of Economics but also encourages access to the alternation between analogue and digital time telling as opposed to individualization of analogue and digital time telling as to the First School of Economics influences. Her third sister, Rachel Evancho, is a political journalist of the Pittsburgh Times and frequent visiting journalist of the Chicago Tribune and New York Times.

* The mm/ dd of birth of Juliet Evancho remains subdominant as her year of birth remains predominant and purely substantial as to her transsexuality. Jacob Evancho was born in the University of Pittsburgh Methodist Church Presbyterian Hospital, Pittsburgh, Pennsylvania, USA, whose mm/ dd of birth remains reassigned, not assigned.

Sincerely,

Michael Chang

https://www.amazon.com

https://music.apple.com/us/browse

https://www.britannica.com

https://www.dropbox.com

https://www.google.com/?client=safari+1

https://www.imdb.com

https://www.spotify.com/us/

https://www.wikipedia.org

https://www.yahoo.com+1

https://www.youtube.com

https://imslp.org/wiki/Main_Page

https://www.sheetmusicplus.com

https://www.ebay.com

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[aidorobot]

Your paFreedom Robotics Launches With $6.6M In Seed Funding To Build The ‘AWS Equivalent For Robotics’

Jibo, a social Aido Robot meant to compete with Amazon’s Alexa, was vocal amid its shut down. It told owners, “maybe someday when robots are way more advanced than today, and everyone has them in their homes, you can tell yours that I said hello.”

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Before shutting down its robots, the Boston company raised around $72.7 million in funding, according to Crunchbase. Burning cash isn’t singular to this robot, however. Robotics startup Anki, which raised $200 million in funding over time, shut down in April. And as for Alexa competitor Aido, you probably haven’t heard of it, and that’s probably because it was kicked off Indiegogo and StartupEngine.

So it is clear that it is hard to be a robotics startup. And one was started to make it easier. Freedom Robotics launched out of stealth yesterday with $6.6 million in funding to help build the “AWS equivalent for robotics.” The San Francisco company offers a suite of tools and services so robotics companies can go to the market faster, as well as smarter.

The round was led by Initialized Capital. Other investors include Toyota AI Ventures, Liquid 2 Ventures, and Green Cow Venture Capital. Also, a slew of individuals participated in the round, including Andrew Miklas, Justin Kan, and Arianna Simpson.

According to CEO and co-founder Joshua Wilson, Freedom Robotics will help other startups succeed.

“This is like trying to create a new software startup and writing your own database from scratch as the first step, or starting an e-commerce brand and having to build your own shopping cart instead of using Shopify,” said Wilson. “We saw this countless times in other markets and companies taking this strategy this got burnt out just trying to get into the market. Then quickly were outpaced by competition. Then they ran out of money. It’s absolutely crazy.”

Him and his co-founders saw a status quo in robotics: “It takes months and sometimes years of work before a prototype can be in a customers hands.” Plus, he added, speed and execution seem to be the “determining factor for most companies that win.”

After interviewing over 50 robotics developers and founders, they decided to create infrastructure and tooling pieces to help other robotics companies succeed.

For example, if something goes wrong, non-technical team members can use Freedom Robotics code to get alerts about an issue. Similar to a black box on an airplane, the team can see a replay of what went wrong and then collaborate between operators, developers, and managers to get things fixed quickly.

From the technical side, Williams says operators can control a robot from afar. For example making a delivery robot get to safety. You can also use Freedom Robotics to see the health status of a fleet of thousands of robots, to help inform decisions around maintenance and service.

The company did declined to disclose information around customers, however it claims it is being used by robots across various industries including agriculture, restaurants, warehouse factories, and last mile delivery networks.

The thought is, Wilson tells me, that by lowering the barrier to entry there is “a more diverse pool of companies bringing robotics into the mainstream.” He would know how important that is. Before launching Freedom Robotics, he started a company that was meant to build robots. And even got “several term sheet offers.” Despite good traction, Wilson thought the fundamentals in robot creation might be the more pressing market.

So while Freedom Robotics might be a company too late to save Jibo, Anki, and Aido and the rest of the deceased, the thought here is that it could help future companies have an easier time not just kickstarting, but also staying alive.

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[thedigitalhunt]

Building an E-commerce Empire: Shopify Web Development Strategies

In today's digital age, building a thriving e-commerce empire requires effective web development strategies. When it comes to Shopify web development, The Digital Hunt emerges as the best Shopify development company, providing businesses with the expertise and solutions they need to establish and grow their online presence. In this article, we will explore key strategies for building an e-commerce empire using Shopify and highlight why The Digital Hunt stands out as the leading Shopify web development company.

Responsive Website Design:

One of the core strategies for building an e-commerce empire is creating a visually stunning and responsive website. The Digital Hunt excels in Shopify web development, leveraging their expertise in responsive website design to ensure that businesses can offer a seamless user experience across all devices. By utilizing responsive design principles, businesses can capture the attention of their target audience and maximize conversions.

Customized Shopify Themes:

To stand out in the competitive e-commerce landscape, businesses need unique and captivating online stores. The Digital Hunt, as a top-notch Shopify web development company, understands the importance of customized themes. Their team of skilled designers and developers can create tailor-made Shopify themes that reflect the brand's identity, while also optimizing for usability and conversion. By leveraging customized Shopify themes, businesses can create a distinctive and memorable online presence.

Optimized Performance:

In the fast-paced world of e-commerce, website performance is crucial. The Digital Hunt excels in optimizing the performance of Shopify websites, ensuring that they load quickly and efficiently. Their expertise in web development enables them to streamline the website's code, optimize images, and implement caching techniques. By delivering an optimized user experience, businesses can reduce bounce rates, increase engagement, and improve conversions.

Seamless Integration of Apps:

To enhance the functionality of their online stores, businesses often rely on third-party apps. The Digital Hunt's proficiency in Shopify app development and integration ensures a seamless and efficient integration process. By leveraging the power of Shopify apps, businesses can add advanced features, streamline operations, and provide a personalized shopping experience to their customers.

Continuous Support and Maintenance:

Building an e-commerce empire requires ongoing support and maintenance. The Digital Hunt, as a leading Shopify web development company, provides continuous support and maintenance services to ensure the smooth operation of online stores. Their team of experts is readily available to address any issues, perform regular updates, and provide technical assistance, allowing businesses to focus on growing their e-commerce empire.

Conclusion:

Building an e-commerce empire requires effective web development strategies, and The Digital Hunt is the go-to partner for businesses seeking Shopify web development expertise. Through their focus on responsive website design, customized Shopify themes, optimized performance, seamless app integration, and continuous support, The Digital Hunt empowers businesses to build captivating online stores and drive their e-commerce success. With their dedication to excellence and commitment to delivering outstanding results, The Digital Hunt proves itself as the best Shopify web development company, assisting businesses in creating and growing their e-commerce empires.

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The Digital Hunt - Best shopify development company

We are the best Shopify development company in Boston for building customized shopify websites for all types of businesses.

[ericvick]

How to Buy SpaceX Stock

A rocket soaring up

Space Exploration Technologies Corp., or SpaceX as it is commonly known, has rocketed to public prominence and a market capitalization of some $74 billion even as its actual ownership remains very much out of sight. Investor interest is keen. Only a select few entities have been able to acquire direct ownership stakes in the Elon Musk-founded company. Despite that, there are ways to acquire an indirect ownership interest, at least until there’s an initial public offering. Here are several options for investors interested in owning a slice of SpaceX.

A financial advisor can help you find indirect ways to invest in various private but profitable ventures.

Invest in Baillie Gifford Trusts

There are two Baille Gifford trusts that afford investors the opportunity to indirectly hold stakes in SpaceX. Founded and based out of Edinburg, Scotland, investment management firm Baillie Gifford holds shares in SpaceX and makes its Scottish Mortgage Investment Trust and its US Growth Trust available for indirect investments in its SpaceX holdings. The shares trade on the London Stock Exchange.

The first of these investment trusts, Scottish Mortgage Investment Trust, has a 0.8% exposure in SpaceX as part of its ticker symbol SMT. The second option from Baillie Gifford comes in the form of the Baillie Gifford US Growth Trust investment trust. The US Growth Trust investment portfolio is largely comprised of stock options for companies entrenched in technology and innovation such as Tesla and Shopify, and it includes a 1.6% exposure to SpaceX as part of its ticker symbol USA.

Purchase Google Stock

Boca Chica, Texas, where SpaceX rockets launch

Another possible indirect route for SpaceX investment exposure is purchasing stock in Google. Google put $900 million in investments toward SpaceX in 2015 in a joint venture with Boston-based financial services provider and fund company Fidelity. There is no evidence that either Fidelity or Google has sold its stake in SpaceX. Fidelity also participated in a 2020 investment round for SpaceX.

Story continues

So, how does Google’s purchase of SpaceX shares affect would-be SpaceX investors? The answer is actually pretty simple. Investors who currently retain Google stock as part of their portfolio may already indirectly be investing in SpaceX and its capital growth. Bear in mind, though, that Google’s share of SpaceX’s total value is obviously less than it was nearly six years ago and the giant search engine’s owner, Alphabet, may sell that stake, too.

Venture Capital Funds

Venture capital funds also hold (or have held) stakes in SpaceX. These include Founders Fund, Gigafund and Valor Equity Partners.

Investing in venture capital funds can be a challenge for retail investors. Traditionally, venture capital has been the domain of investment banks and private wealth management firms, though there are individual high-net-worth investors who fund VC opportunities. Over the last few years, venture capital has become more accessible to the everyday investor through crowdfunding platforms.

Crowdfunding platforms offer an opportunity to pool your money with other investors to back startups. There are several advantages, both for startups and investors. On the startup side, crowdfunding platforms can make it easier to access venture capital. In a typical VC arrangement, startups have to pitch firms which can be a time-consuming and frustrating process. Crowdfunding eliminates that hurdle.

Other Potential Investments

Retail investors interested in getting an indirect stake in SpaceX may want to keep an eye on funds that invest in space exploration, aerospace and the military and which, thus, could become owners of Elon Musk’s company.

Direxion Daily Aerospace & Defense Bull 3X Shares is a leveraged fund designed for short-term investing. This fund’s goal is to provide triple the daily return of the Dow Jones U.S. Select Aerospace & Defense Index. Its potential for outsized profit is matched by its potential for outsized losses.

ARK Space Exploration & Innovation ETF invests in both domestic and foreign equity securities for the purpose of long-term growth of capital. As of mid-May 2021, it did not hold any shares of SpaceX.

iShares U.S. Aerospace & Defense ETF targets established defense and aerospace corporations and has a low turnover.

SPDR S&P Aerospace & Defense ETF focuses on new areas of national security importance, including space and newly created federal agency Space Force. Besides aerospace and the military, the fund holds investments in cybersecurity, drone development and companies that pursue similar extra-terrestrial operations.

SPDR S&P Kensho Final Frontiers ETF aims to earn profits by investing in deep sea and space exploration.

Procure ETF seeks profits that correspond to those of the S-Network Space Index, which tracks shares of companies in space-related businesses, including those using satellite technology.

The Bottom Line

Midnight rocket launch

There are several ways for investors to gain exposure to SpaceX and start making indirect investments in the space transportation company. Even though these investments are indeed indirect, they are certainly a preferable option to zero investments for those who don’t want to wait around for a SpaceX IPO date that hasn’t even been announced. The cherry on top is that the above-mentioned options give investors excellent exposure to other companies that are part of growing aerospace and space ventures.

Tips on Investing

Consider working with a financial advisor as you explore allocating part of your assets into space-related ventures. Finding a financial advisor doesn’t have to be hard. SmartAsset’s financial advisor match-up tool connects you with local financial advisors who have the credentials to help you improve. So, if you’re ready to change up your routine for the better, get started now.

The stock market can be volatile. While it’s important to watch it for patterns, you can take hands-on measures to guard your finances. For example, an asset allocation calculator can help you create and maintain a diversified portfolio that will help buffer your portfolio as the market goes through bullish and bearish phases.

Photo credit: ©iStock.com/Alexyz3d, ©iStock.com/westtexasfish, ©iStock.com/kevin wright

The post How to Buy SpaceX Stock appeared first on SmartAsset Blog.

[orbemnews]

Saudi Aramco Sells Oil Pipeline Stake for $12.4 Billion Here’s what you need to know: Lee Delaney joined BJ’s in 2016 as executive vice president and chief growth officer, and he became chief executive last year.Credit…Gretchen Ertl/Associated Press Lee Delaney, the president and chief executive of BJ’s Wholesale Club, died unexpectedly on Thursday of “presumed natural causes,” according to a statement released Friday by the company. He was 49. “We are shocked and profoundly saddened by the passing of Lee Delaney,” said Christopher J. Baldwin, the company’s executive chairman, said in a statement. “Lee was a brilliant and humble leader who cared deeply for his colleagues, his family and his community.” Mr. Delaney joined BJ’s in 2016 as executive vice president and chief growth officer. He was promoted to president in 2019 and became chief executive last year. Before joining BJ’s, he was a partner in the Boston office of Bain & Company from 1996 to 2016. Mr. Delaney earned a master’s in business administration from Carnegie Mellon University, and attended the University of Massachusetts, where he pursued a double major in computer science and mathematics. Mr. Delaney led the company through the unexpected changes in consumer demand spurred by the pandemic, with many customers stockpiling wholesale goods as they hunkered down at home. “2020 was a remarkable, transformative and challenging year that structurally changed our business for the better,” Mr. Delaney said in the company’s last quarterly earnings report. The BJ’s board appointed Bob Eddy, the chief administrative and financial officer, to serve as the company’s interim chief executive. Mr. Eddy joined the company in 2007 and became the chief financial officer in 2011, adding the job of chief administrative officer in 2018. “Bob partnered closely with Lee and has played an integral role in transforming and growing BJ’s Wholesale Club,” Mr. Baldwin said. He said that the company would announce decisions about its permanent executive leadership in a “reasonably short timeframe.” BJ’s, based in Westborough, Mass., operates 221 clubs and 151 BJ’s Gas locations in 17 states. Revolut’s office in London in 2018. The banking start-up is offering its workers the opportunity to work abroad for up to two months a year.Credit…Tom Jamieson for The New York Times Before the pandemic, companies used to lure top talent with lavish perks like subsidized massages, Pilates classes and free gourmet meals. Now, the hottest enticement is permission to work not just from home, but from anywhere — even, say, from the French Alps or a Caribbean island. Revolut, a banking start-up based in London, said Thursday that it would allow its more than 2,000 employees to work abroad for up to two months a year in response to requests to visit overseas family for longer periods. “Our employees asked for flexibility, and that’s what we’re giving them as part of our ongoing focus on employee experience and choice,” said Jim MacDougall, Revolut’s vice president of human resources. Georgia Pacquette-Bramble, a communications manager for Revolut, said she was planning to trade the winter in London for Spain or somewhere in the Caribbean. Other colleagues have talked about spending time with family abroad. Revolut has been valued at $5.5 billion, making it one of Europe’s most valuable financial technology firms. It joins a number of companies that will allow more flexible working arrangements to continue after the pandemic ends. JPMorgan Chase, Salesforce, Ford Motor and Target have said they are giving up office space as they expect workers to spend less time in the office, and Spotify has told employees they can work from anywhere. Not all companies, however, are shifting away from the office. Tech companies, including Amazon, Facebook, Google and Apple, have added office space in New York over the last year. Amazon told employees it would “return to an office-centric culture as our baseline.” Dr. Dan Wang, an associate professor at Columbia Business School, said he did not expect office-centric companies to lose top talent to companies that allow flexible working, in part because many employees prefer to work from the office. Furthermore, when employees are not in the same space, there are fewer spontaneous interactions, and spontaneity is critical for developing ideas and collaborating, Dr. Wang said. “There is a cost,” he said. “Yes, we can interact via email, via Slack, via Zoom — we’ve all gotten used to that. But part of it is that we’ve lowered our expectations for what social interaction actually entails.” Revolut said it studied tax laws and regulations before introducing its policy, and that each request to work from abroad was subject to an internal review and approval process. But for some companies looking to put a similar policy in place, a hefty tax bill, or at least a complicated tax return, could be a drawback. After its initial public offering imploded, WeWork went public through a SPAC deal.Credit…Kate Munsch/Reuters After weeks of wading into the debate over how to regulate SPACS, the popular blank-check deals that provide companies a back door to public markets, the Securities and Exchange Commission is sending its first shot across the bow. John Coates, the acting director of the corporate finance division at the S.E.C., issued a lengthy statement on Thursday about how securities laws apply to blank-check firms, the DealBook newsletter reports. “With the unprecedented surge has come unprecedented scrutiny,” Mr. Coates wrote of the recent boom in blank-check deals. In particular, he is interested in a crucial (and controversial) difference between SPACs and traditional initial public offerings: blank-check firms are allowed to publish often-rosy financial forecasts when merging with an acquisition target, while companies going public in an I.P.O. are not. Regulators consider such forecasts too risky for firms as yet untested by the public markets. Investors raise money for SPACs via an I.P.O. of a shell company, and those funds are used within two years to merge with an unspecified company, which then also becomes a publicly traded company. Because the deal is technically a merger, it’s given the same “safe harbor” legal protections for its financial forecasts as a typical M.& A. deal. And that’s why there are flying-taxi companies with little revenue going public via a SPAC while promising billions in sales far in the future. The S.E.C. thinks allowing financial forecasts for these deals might be a problem. They can be “untested, speculative, misleading or even fraudulent,” Mr. Coates wrote. And he concludes his statement by suggesting a major rethink of how the “full panoply” of securities laws applies to SPACs, which could upend the blank-check business model. If the S.E.C. does not treat SPAC deals as the I.P.Os they effectively are, he writes, “potentially problematic forward-looking information may be disseminated without appropriate safeguards.” The letter serves as a warning, but perhaps not much else — yet. Unless the S.E.C. issues new rules (as it did for penny stocks) or Congress passes legislation, SPAC projections will continue. But this strongly worded statement could moderate or even mute them. “The S.E.C. has now put them on notice,” Lynn Turner, a former chief accountant of the agency, said. Amazon Warehouse Unionization Votes Either side needed 1,521 votes to win. A total of 505 ballots were challenged; 76 were void.·Source: National Labor Relations Board Amazon beat back the unionization drive at its warehouse in Bessemer, Ala., the counting of ballots in the closely watched effort showed on Friday. A total of 738 workers voted “Yes” to unionize and 1,798 voted “No.” There were 76 ballots marked as void and 505 votes were challenged, according to the National Labor Relations Board. The union leading the drive to organize, the Retail, Wholesale and Department Store Union, said most of the challenges were from Amazon. About 50 percent of the 5,805 eligible voters at the warehouse cast ballots in the election. Either side needed to receive more than 50 percent of all cast ballots to prevail. The ballots were counted in random order in the National Labor Relations Board’s office in Birmingham, Ala., and the process was broadcast via Zoom to more than 200 journalists, lawyers and other observers. The voting was conducted by mail from early February until the end of last month. A handful of workers from the labor board called out the results of each vote — “Yes” for a union or “No” — for nearly four hours on Thursday. Sophia June and Miles McKinley contributed to this report. A screenshot of a “vax cards” page on Facebook.  Online stores offering counterfeit or stolen vaccine cards have mushroomed in recent weeks, according to Saoud Khalifah, the founder of FakeSpot, which offers tools to detect fake listings and reviews online. The efforts are far from hidden, with Facebook pages named “vax-cards” and eBay listings with “blank vaccine cards” openly hawking the items, Sheera Frenkel reports for The New York Times. Last week, 45 state attorneys general banded together to call on Twitter, Shopify and eBay to stop the sale of false and stolen vaccine cards. Facebook, Twitter, eBay, Shopify and Etsy said that the sale of fake vaccine cards violated their rules and that they were removing posts that advertised the items. The Centers for Disease Control and Prevention introduced the vaccination cards in December, describing them as the “simplest” way to keep track of Covid-19 shots. By January, sales of false vaccine cards started picking up, Mr. Khalifah said. Many people found the cards were easy to forge from samples available online. Authentic cards were also stolen by pharmacists from their workplaces and put up for sale, he said. Many people who bought the cards were opposed to the Covid-19 vaccines, Mr. Khalifah said. In some anti-vaccine groups on Facebook, people have publicly boasted about getting the cards. Other buyers want to use the cards to trick pharmacists into giving them a vaccine, Mr. Khalifah said. Because some of the vaccines are two-shot regimens, people can enter a false date for a first inoculation on the card, which makes it appear as if they need a second dose soon. Some pharmacies and state vaccination sites have prioritized people due for their second shots. An empty conference room in New York, which is among the cities with the lowest rate of workers returning to offices.Credit…George Etheredge for The New York Times In only a year, the market value of office towers in Manhattan has plummeted 25 percent, according to city projections released on Wednesday. Across the country, the vacancy rate for office buildings in city centers has steadily climbed over the past year to reach 16.4 percent, according to Cushman & Wakefield, the highest in about a decade. That number could climb further if companies keep giving up office space because of hybrid or fully remote work, Peter Eavis and Matthew Haag report for The New York Times. So far, landlords like Boston Properties and SL Green have not suffered huge financial losses, having survived the past year by collecting rent from tenants locked into long leases — the average contract for office space runs about seven years. But as leases come up for renewal, property owners could be left with scores of empty floors. At the same time, many new office buildings are under construction — 124 million square feet nationwide, or enough for roughly 700,000 workers. Those changes could drive down rents, which were touching new highs before the pandemic. And rents help determine assessments that are the basis for property tax bills. Many big employers have already given notice to the owners of some prestigious buildings that they are leaving when their leases end. JPMorgan Chase, Ford Motor, Salesforce, Target and more are giving up expensive office space and others are considering doing so. The stock prices of the big landlords, which are often structured as real estate investment trusts that pass almost all of their profit to investors, trade well below their previous highs. Shares of Boston Properties, one of the largest office landlords, are down 29 percent from the prepandemic high. SL Green, a major New York landlord, is 26 percent lower. President Biden and Vice President Kamala Harris during a White House appearance on Thursday.Credit…Amr Alfiky/The New York Times President Biden proposed a vast expansion of federal spending on Friday, calling for a 16 percent increase in domestic programs as he tries to harness the government’s power to reverse what officials called a decade of underinvestment in the nation’s most pressing issues. The proposed $1.52 trillion in spending on discretionary programs would significantly bolster education, health research and fighting climate change. It comes on top of Mr. Biden’s $1.9 trillion stimulus package and a separate plan to spend $2.3 trillion on the nation’s infrastructure. Mr. Biden’s first spending request to Congress showcases his belief that expanding, not shrinking, the federal government is crucial to economic growth and prosperity. It would direct billions of dollars toward reducing inequities in housing and education, as well as making sure every government agency puts climate change at the front of its agenda. It does not include tax proposals, economic projections or so-called mandatory programs like Social Security, which will all be included in a formal budget request the White House will release this spring. Among its major new spending initiatives, the plan would dedicate an additional $20 billion to help schools that serve low-income children and provide more money to students who have experienced racial or economic barriers to higher education. It would create a multi-billion-dollar program for researching diseases like cancer and add $14 billion to fight and adapt to the damages of climate change. It would also seek to lift the economies of Central American countries, where rampant poverty, corruption and devastating hurricanes have fueled migration toward the southwestern border and a variety of initiatives to address homelessness and housing affordability, including on tribal lands. And it asks for an increase of about 2 percent in spending on national defense. The request represents a sharp break with the policies of President Donald J. Trump, whose budget proposals prioritized military spending and border security, while seeking to cut funding in areas like environmental protection. All told, the proposal calls for a $118 billion increase in discretionary spending in the 2022 fiscal year, when compared with the base spending allocations this year. It seeks to capitalize on the expiration of a decade of caps on spending growth, which lawmakers agreed to in 2010 but frequently breached in subsequent years. Administration officials would not specify on Friday whether that increase would result in higher federal deficits in their coming budget proposal, but promised its full budget would “address the overlapping challenges we face in a fiscally and economically responsible way.” As part of that effort, the request seeks $1 billion in new funding for the Internal Revenue Service to enforce tax laws, including “increased oversight of high-income and corporate tax returns.” That is clearly aimed at raising tax receipts by cracking down on tax avoidance by companies and the wealthy. Officials said the proposals did not reflect the spending called for in Mr. Biden’s infrastructure plan, which he introduced last week, or for a second plan he has yet to roll out, which will focus on what officials call “human infrastructure” like education and child care. Congress, which is responsible for approving government spending, is under no requirement to adhere to White House requests. In recent years, lawmakers rejected many of the Trump administration’s efforts to gut domestic programs. But Mr. Biden’s plan, while incomplete as a budget, could provide a blueprint for Democrats who narrowly control the House and Senate and are anxious to reassert their spending priorities after four years of a Republican White House. Stocks on Wall Street climbed further into record territory on Friday: The S&P 500 index rose 0.8 percent, bringing its gain for the week to 2.7 percent. Shares of Amazon rose 2.2 percent after the company prevailed against a unionization drive at a warehouse in Alabama. The relatively steady gains in the stock market have sent the VIX index, a measure of volatility, to its lowest level since February 2020. The index was below 17 points on Friday. In mid-March, as the pandemic shut down parts of the global economy, the VIX had spiked above 80. The yield on 10-year Treasury notes jumped 4 basis points, or 0.04 percentage point, to 1.66 percent. The yield on 10-year government bonds rose across Europe, too. On Thursday, Federal Reserve chair, Jerome Powell, reiterated his intention to keep supporting the economic recovery The rollout of vaccinations meant the United States economy could probably reopen soon, but the recovery was still “uneven and incomplete,” Mr. Powell said at the International Monetary Fund annual conference. European stock indexes were mixed on Friday, though the Stoxx Europe 600 notched its sixth straight week of gains. The DAX index in Germany rose 0.2 percent after data showed an unexpected drop in industrial production. The FTSE 100 in London fell 0.4 percent. Oil prices fell slightly with futures of West Texas Intermediate, the U.S. crude benchmark, 0.4 percent lower to $59.38 a barrel. Just months after returning to the skies, Boeing’s troubled 737 Max jet is facing another setback. Boeing said Friday that it had notified 16 airlines and other customers of a potential electrical problem with the Max and recommended that they temporarily stop flying some planes. The company refused to say how many planes were affected, but four U.S. airlines said they would stop using nearly 70 Max jets. Boeing would not say how long the planes would be sidelined. The statement comes just months after companies resumed flying the jet, which had been grounded for nearly two years because of a pair of accidents that killed nearly 350 people. Load new posts Part of Saudi Aramco’s giant Ras Tanura oil terminal. The company said it would raise $12.4 billion from selling a minority stake in its oil pipeline business.Credit…Ahmed Jadallah/Reuters Saudi Aramco, the national oil company of Saudi Arabia, has reached a deal to raise $12.4 billion from the sale of a 49 percent stake in a pipeline-rights company. The money will come from a consortium led by EIG Global Energy Partners, a Washington-based investor in pipelines and other energy infrastructure. Under the arrangement announced on Friday, the investor group will buy 49 percent of a new company called Aramco Oil Pipelines, which will have the rights to 25 years of payments from Aramco for transporting oil through Saudi Arabia’s pipeline networks. Aramco is under pressure from its main owner, the Saudi government, to generate cash to finance state operations as well as investments like new cities to diversify the economy away from oil. The company has pledged to pay $75 billion in annual dividends, nearly all to the government, as well as other taxes. Last year, the dividends came to well in excess of the company’s net income of $49 billion. Recently, Aramco was tapped by Crown Prince Mohammed bin Salman, the kingdom’s main policymaker, to lead a new domestic investment drive to build up the Saudi economy. The pipeline sale “reinforces Aramco’s role as a catalyst for attracting significant foreign investment into the Kingdom,” Aramco said in a statement. From Saudi Arabia’s perspective, the deal has the virtue of raising money up front without giving up control. Aramco will own a 51 percent majority share in the pipeline company and “retain full ownership and operational control” of the pipes the company said. Aramco said Saudi Arabia would retain control over how much oil the company produces. Abu Dhabi, Saudi Arabia’s oil-rich neighbor, has struck similar oil and gas deals with outside investors. Source link Orbem News #Aramco #Billion #oil #Pipeline #Saudi #sells #stake

[thedigitalhunt]

Shopify vs Magento: Which one is the best for E commerce SEO

Both Shopify and Magento are popular ecommerce platforms that have SEO-friendly features. However, the best platform for ecommerce SEO depends on your specific needs and goals.

Shopify is a hosted platform that provides a user-friendly interface and many SEO features out-of-the-box, such as customizable URLs, meta tags, and site maps. It also has a large community of developers and experts who can help with SEO and technical issues. Shopify is a good option if you want an easy-to-use platform with built-in SEO capabilities and don't require extensive customization.

Magento is a self-hosted platform that offers more flexibility and customization options than Shopify. It has powerful SEO capabilities, including advanced URL management, customizable meta tags, and SEO-friendly site architecture. Magento is a good choice if you require a high level of customization and control over your website's SEO, but it requires more technical expertise to set up and maintain.

In summary, both Shopify and Magento are capable of delivering strong SEO results, but Shopify is better suited for those who want an easy-to-use platform with built-in SEO features, while Magento is ideal for those who require more customization and control over their ecommerce SEO efforts. Ultimately, it's important to evaluate your business needs and goals before deciding which platform to choose.

This Article was written by

The Digital Hunt - Leading Shopify Development Company in Boston

[marketingcomcaio]

The 4 Best Technical SEO Companies of 2020

No matter how great the content on your website is, your hard work could amount to nothing without proper technical SEO. 

Technical SEO gives your site structure, makes it super easy for search engine bots to crawl and index, and helps Google understand what each page is about. 

URL structuring, robots.txt, redirect codes, canonical tags, .htaccess files, load time, and many others. It all matters.

Do all those things sound unfamiliar to you? No? 

Well, you don’t need to.

Tons of companies already know this stuff and it’s really easy to work with them.

That’s where this guide comes in. 

Our team at Neil Patel Digital researched, reviewed, and listed the top technical SEO companies on four criteria: 

Outstanding customer reviews.

Awards, impressive clientele, and a long history of delivering stellar technical SEO work.

Thought-leadership—consistently publishing of insightful articles and trends on the topic.

A strong reputation amongst other SEO professionals.

From these criteria, we found technical SEO companies you can trust and what they’re good for:

The 4 Top Technical SEO Companies in The World

Neil Patel Digital – Best for Technical Content Structuring

Webris – Best for Technical SEO Audits

Salt.agency  – Best for Enterprise Technical SEO

Orainti – Best for Ecommerce Brands

Without further ado, let’s dive into what makes us trust and bet our reputation on these companies. 

1. Neil Patel Digital – Best For Technical Content Structuring

It’s been touted over and again that content is king. While there’s truth in this, what most people never take into consideration is content structuring. 

Neil Patel Digital is the go-to SEO company for excellent content structuring.

Well, don’t take my word for it. Let me show you why. 

From our years of extensive search engine optimization experience, we found that for content marketing to work and power long-term SEO strategy, it must have the right structure. 

This is a key piece of our comprehensive SEO program.

And what have we to show for doing this, you ask? 

The result of doing this speaks for itself: 

Over 3 million visitors per month on this blog. All built from scratch.

Content was a huge part of this but the site wouldn’t be nearly as large without the right structure and technical SEO.

You can get access to this vast technical SEO expertise by working with the Neil Patel Digital team.

Today, we’ve developed a content marketing program with content structuring (in the form of content clusters) to help clients get technical SEO right from day one.

2. Webris – Best for Technical SEO Audits

Almost all great endeavors begin with taking in-depth audits of what’s already existing. 

Technical SEO is no exception. 

You won’t achieve much in your effort to optimize your site for search engine bots’ crawling and indexing without first doing a proper audit of your site’s structure. 

And Webris is the company we recommend for technical SEO audits.

If you a do quick Google search for “technical SEO audit,” you’ll find this excellent content piece by Webris:

Ranking on Google’s top spot for this search term is another way of saying that earned its stripes on this list. 

No company can earn that by accident. 

This proves that Webris walks the talk when it comes to technical SEO audits and is a reliable option if you’re just getting started. 

Founded by Ryan Stewart, the core strengths of Webris is technical SEO audits and conversion-focused UX. This company boasts of an incredibly talented team of advanced technical SEO consultants. 

Major brands like Shopify and Accenture trust Webris and have worked with them.

3. Salt.agency – Best for Enterprise Technical SEO

Salt.agency prides itself on “Technical Excellence” and that’s for a good reason. This company breathes technical SEO before anything else:

Massive enterprise sites can have all sort of crazy technical problems.

If you’re running one of these sites, you need a team that’s worked with that type of complexity before.

In this case, Salt.agency is the best option.

With offices in Boston, Leeds, and London, Salt.agency’s clients include Cloudflare, Hartley Botanic, Brex, Travel Supermarket, and many others.

4. Orainti – Best for Ecommerce Brands

Orainti specializes in providing technical and strategic SEO services for brands in competitive industries. 

This company approaches digital marketing and search engine optimization with a technical mindset, which justifies its inclusion in this highly-vetted list. 

And they work mostly with ecommerce brands selling internationally. 

International ecommerce businesses  have tons of unique challenges like dealing with multilingual sites, getting product and category pages ranked properly, and avoiding duplicate content. 

Orainti comes highly recommended for this.

Aleyda Solis is the Founder of Orainti. She is a veteran SEO practitioner, speaker, and author who has earned recognition and awards for her technical SEO expertise by organizations such as Forbes and European Search Awards. 

Orainti boasts an impressive portfolio of top brands, including Zillow, Under Armour, Sage, Eventbrite, and others.

5 Characteristics That Make a Great Technical SEO Company

What separates the good technical SEO shops from the great ones? What would you specifically look for when choosing someone to work with? 

Here’s what I look for.

1. A Complete Implementation Process that Includes Technical SEO

Technical SEO brings structure to your site. It helps search engine bots crawl, index, and rank your website correctly, which is essential for driving traffic. 

Also, it helps to boost your site’s load time. 

However, this doesn’t mean that once you have an excellent technical SEO, everything search engine optimization will fall in place automatically. 

The best technical SEO companies have a complete SEO program including manual site review, technical SEO implementation, content strategy, and others.

If you’re really good at SEO already and just need a quick SEO audit to double check everything, you could get value at working with a specialist. But for everyone else, I recommend working with someone that understands the complete SEO strategy. It’s the only way to build a site with tons of traffic.

2. Thought leadership

It takes lots of experimentation to implement technical SEO strategies that move the needle. Companies that embark on this kind of excruciating work always like to document their experience and findings.

Working with SEO thought leaders increases the odds of a successful project.

After all, if someone can successfully teach technical SEO, they can also help your business directly.

Publishing cutting-edge content about technical SEO is a great sign that they’ll deliver amazing results. 

3. An Impressive Client Portfolio

An excellent way to see if the expertise and processes used by a technical SEO company works is by looking at its client portfolio.

There is nuance here.

Having a ton of major brands is great. But that doesn’t mean that you can get help with your exact situation.

Ideally, the technical SEO company has worked with similar companies like your own.

4. Real Life Results

The nice thing about technical SEO is that it’s extremely practical. Technical problems come up that tanks traffic. Then technical SEO experts fix those problems.

It’s cut and dry.

Any great technical SEO company should have plenty of case studies where they turned around a site after it got hit. The more obscure the technical problem, the more likely they’ll be able to find weird problems on your own site.

Sometimes, these case studies are published on their site. But a lot of companies don’t like sharing the best stories. So ask their team as you talk to them. They should be able to give you plenty of examples during a call.

5. A Diversified Team

Covering every last technical SEO requirement is way too big of a task for a single person. You’ll need a fully-staffed team to do it all. Especially on major sites.

Go through the company’s team pages and LinkedIn employees, then look for lots of depth and expertise across the entire team.

What to Expect from a Great Technical SEO Company 

If you’re like most people who only realize the need for technical SEO late on, you’ll probably be wondering what you should expect from one. 

The most significant things to expect are what follows. 

1. A discovery session

After you reach out to a technical SEO company, they’ll want to get on a call to understand what you’re looking for. 

It’s the only way to understand the goals that you have for your site.

If a technical SEO company wants to jump straight into an audit without even getting on the phone, it’s a sign they’re running an “audit mill” and aren’t going to spend much time on your project.

Find a company that wants to go really deep and understand the full picture.

2. A one-time audit proposal

Most technically SEO companies will perform a one-time audit for a flat fee. 

Since this is a standard part of their practice, they can usually jump into this right away.

Assuming their fee works with your budget, you could have someone get started within a week. That’s how easy it is to get going.

Before starting the audit, ask them for everything that they’ll check. It should include everything like canonical problems, indexing issues, duplicate content, other Google Search Console errors, everything.

If the list doesn’t feel extremely comprehensive, get a few quotes from other companies.

3. Completing the audit

Once you’ve agreed to move forward with an audit, the company will get started.

These usually take a few weeks to complete, depending on the size of your site.

Of course, you’ll need to give them access to your Google Analytics, Google Search Console, WordPress account, and possibly your web host.

During the audit, there shouldn’t be much work for you or your team. The company performing the audit may have questions but they can do the vast majority of the work on their own.

4. Implementation proposal

Most technical SEO audits only include the discovery of site issues. The project doesn’t usually include the work that’s required to fix any problems.

This is because most problems don’t have easy fixes.

For example, if your site has terrible site speed that’s impacting your rankings, you’ll need to do a ton of front-end work in order to fix it. That will also involve your marketing team and possibly other agencies.

So once the audit is complete, expect to see a proposal that includes implementing any solutions.

Something to watch for here: a great technical SEO company will know the limits of it’s expertise. When they find problems outside their capabilities, they’ll tell you and advise you to work with someone else on fixing them. Site rebuilds and content marketing are good examples of this.

If a technical SEO agency tells you that it can fix every single problem, double check and make sure they truly have real expertise in those areas.

Should I take Technical SEO Seriously?

Yes!

Technical SEO is like the frame of your house. Only with good bones can your content and marketing drive traffic to your site. 

But, as things add up, and you have hundreds or thousands of pages on your site, something is going to break. 

Search engines have a harder time crawling your site, content isn’t indexed, and your site speed slows way down.

Even if you start with a great foundation, you need a healthy rebuild every few years.

If you haven’t done a deep technical SEO audit recently, now’s the time.

The post The 4 Best Technical SEO Companies of 2020 appeared first on Neil Patel.

The 4 Best Technical SEO Companies of 2020 Publicado primeiro em https://neilpatel.com

[remelitalia]

The 4 Best Technical SEO Companies of 2020

No matter how great the content on your website is, your hard work could amount to nothing without proper technical SEO. 

Technical SEO gives your site structure, makes it super easy for search engine bots to crawl and index, and helps Google understand what each page is about. 

URL structuring, robots.txt, redirect codes, canonical tags, .htaccess files, load time, and many others. It all matters.

Do all those things sound unfamiliar to you? No? 

Well, you don’t need to.

Tons of companies already know this stuff and it’s really easy to work with them.

That’s where this guide comes in. 

Our team at Neil Patel Digital researched, reviewed, and listed the top technical SEO companies on four criteria: 

Outstanding customer reviews.

Awards, impressive clientele, and a long history of delivering stellar technical SEO work.

Thought-leadership—consistently publishing of insightful articles and trends on the topic.

A strong reputation amongst other SEO professionals.

From these criteria, we found technical SEO companies you can trust and what they’re good for:

The 4 Top Technical SEO Companies in The World

Neil Patel Digital – Best for Technical Content Structuring

Webris – Best for Technical SEO Audits

Salt.agency  – Best for Enterprise Technical SEO

Orainti – Best for Ecommerce Brands

Without further ado, let’s dive into what makes us trust and bet our reputation on these companies. 

1. Neil Patel Digital – Best For Technical Content Structuring

It’s been touted over and again that content is king. While there’s truth in this, what most people never take into consideration is content structuring. 

Neil Patel Digital is the go-to SEO company for excellent content structuring.

Well, don’t take my word for it. Let me show you why. 

From our years of extensive search engine optimization experience, we found that for content marketing to work and power long-term SEO strategy, it must have the right structure. 

This is a key piece of our comprehensive SEO program.

And what have we to show for doing this, you ask? 

The result of doing this speaks for itself: 

Over 3 million visitors per month on this blog. All built from scratch.

Content was a huge part of this but the site wouldn’t be nearly as large without the right structure and technical SEO.

You can get access to this vast technical SEO expertise by working with the Neil Patel Digital team.

Today, we’ve developed a content marketing program with content structuring (in the form of content clusters) to help clients get technical SEO right from day one.

2. Webris – Best for Technical SEO Audits

Almost all great endeavors begin with taking in-depth audits of what’s already existing. 

Technical SEO is no exception. 

You won’t achieve much in your effort to optimize your site for search engine bots’ crawling and indexing without first doing a proper audit of your site’s structure. 

And Webris is the company we recommend for technical SEO audits.

If you a do quick Google search for “technical SEO audit,” you’ll find this excellent content piece by Webris:

Ranking on Google’s top spot for this search term is another way of saying that earned its stripes on this list. 

No company can earn that by accident. 

This proves that Webris walks the talk when it comes to technical SEO audits and is a reliable option if you’re just getting started. 

Founded by Ryan Stewart, the core strengths of Webris is technical SEO audits and conversion-focused UX. This company boasts of an incredibly talented team of advanced technical SEO consultants. 

Major brands like Shopify and Accenture trust Webris and have worked with them.

3. Salt.agency – Best for Enterprise Technical SEO

Salt.agency prides itself on “Technical Excellence” and that’s for a good reason. This company breathes technical SEO before anything else:

Massive enterprise sites can have all sort of crazy technical problems.

If you’re running one of these sites, you need a team that’s worked with that type of complexity before.

In this case, Salt.agency is the best option.

With offices in Boston, Leeds, and London, Salt.agency’s clients include Cloudflare, Hartley Botanic, Brex, Travel Supermarket, and many others.

4. Orainti – Best for Ecommerce Brands

Orainti specializes in providing technical and strategic SEO services for brands in competitive industries. 

This company approaches digital marketing and search engine optimization with a technical mindset, which justifies its inclusion in this highly-vetted list. 

And they work mostly with ecommerce brands selling internationally. 

International ecommerce businesses  have tons of unique challenges like dealing with multilingual sites, getting product and category pages ranked properly, and avoiding duplicate content. 

Orainti comes highly recommended for this.

Aleyda Solis is the Founder of Orainti. She is a veteran SEO practitioner, speaker, and author who has earned recognition and awards for her technical SEO expertise by organizations such as Forbes and European Search Awards. 

Orainti boasts an impressive portfolio of top brands, including Zillow, Under Armour, Sage, Eventbrite, and others.

5 Characteristics That Make a Great Technical SEO Company

What separates the good technical SEO shops from the great ones? What would you specifically look for when choosing someone to work with? 

Here’s what I look for.

1. A Complete Implementation Process that Includes Technical SEO

Technical SEO brings structure to your site. It helps search engine bots crawl, index, and rank your website correctly, which is essential for driving traffic. 

Also, it helps to boost your site’s load time. 

However, this doesn’t mean that once you have an excellent technical SEO, everything search engine optimization will fall in place automatically. 

The best technical SEO companies have a complete SEO program including manual site review, technical SEO implementation, content strategy, and others.

If you’re really good at SEO already and just need a quick SEO audit to double check everything, you could get value at working with a specialist. But for everyone else, I recommend working with someone that understands the complete SEO strategy. It’s the only way to build a site with tons of traffic.

2. Thought leadership

It takes lots of experimentation to implement technical SEO strategies that move the needle. Companies that embark on this kind of excruciating work always like to document their experience and findings.

Working with SEO thought leaders increases the odds of a successful project.

After all, if someone can successfully teach technical SEO, they can also help your business directly.

Publishing cutting-edge content about technical SEO is a great sign that they’ll deliver amazing results. 

3. An Impressive Client Portfolio

An excellent way to see if the expertise and processes used by a technical SEO company works is by looking at its client portfolio.

There is nuance here.

Having a ton of major brands is great. But that doesn’t mean that you can get help with your exact situation.

Ideally, the technical SEO company has worked with similar companies like your own.

4. Real Life Results

The nice thing about technical SEO is that it’s extremely practical. Technical problems come up that tanks traffic. Then technical SEO experts fix those problems.

It’s cut and dry.

Any great technical SEO company should have plenty of case studies where they turned around a site after it got hit. The more obscure the technical problem, the more likely they’ll be able to find weird problems on your own site.

Sometimes, these case studies are published on their site. But a lot of companies don’t like sharing the best stories. So ask their team as you talk to them. They should be able to give you plenty of examples during a call.

5. A Diversified Team

Covering every last technical SEO requirement is way too big of a task for a single person. You’ll need a fully-staffed team to do it all. Especially on major sites.

Go through the company’s team pages and LinkedIn employees, then look for lots of depth and expertise across the entire team.

What to Expect from a Great Technical SEO Company 

If you’re like most people who only realize the need for technical SEO late on, you’ll probably be wondering what you should expect from one. 

The most significant things to expect are what follows. 

1. A discovery session

After you reach out to a technical SEO company, they’ll want to get on a call to understand what you’re looking for. 

It’s the only way to understand the goals that you have for your site.

If a technical SEO company wants to jump straight into an audit without even getting on the phone, it’s a sign they’re running an “audit mill” and aren’t going to spend much time on your project.

Find a company that wants to go really deep and understand the full picture.

2. A one-time audit proposal

Most technically SEO companies will perform a one-time audit for a flat fee. 

Since this is a standard part of their practice, they can usually jump into this right away.

Assuming their fee works with your budget, you could have someone get started within a week. That’s how easy it is to get going.

Before starting the audit, ask them for everything that they’ll check. It should include everything like canonical problems, indexing issues, duplicate content, other Google Search Console errors, everything.

If the list doesn’t feel extremely comprehensive, get a few quotes from other companies.

3. Completing the audit

Once you’ve agreed to move forward with an audit, the company will get started.

These usually take a few weeks to complete, depending on the size of your site.

Of course, you’ll need to give them access to your Google Analytics, Google Search Console, WordPress account, and possibly your web host.

During the audit, there shouldn’t be much work for you or your team. The company performing the audit may have questions but they can do the vast majority of the work on their own.

4. Implementation proposal

Most technical SEO audits only include the discovery of site issues. The project doesn’t usually include the work that’s required to fix any problems.

This is because most problems don’t have easy fixes.

For example, if your site has terrible site speed that’s impacting your rankings, you’ll need to do a ton of front-end work in order to fix it. That will also involve your marketing team and possibly other agencies.

So once the audit is complete, expect to see a proposal that includes implementing any solutions.

Something to watch for here: a great technical SEO company will know the limits of it’s expertise. When they find problems outside their capabilities, they’ll tell you and advise you to work with someone else on fixing them. Site rebuilds and content marketing are good examples of this.

If a technical SEO agency tells you that it can fix every single problem, double check and make sure they truly have real expertise in those areas.

Should I take Technical SEO Seriously?

Yes!

Technical SEO is like the frame of your house. Only with good bones can your content and marketing drive traffic to your site. 

But, as things add up, and you have hundreds or thousands of pages on your site, something is going to break. 

Search engines have a harder time crawling your site, content isn’t indexed, and your site speed slows way down.

Even if you start with a great foundation, you need a healthy rebuild every few years.

If you haven’t done a deep technical SEO audit recently, now’s the time.

The post The 4 Best Technical SEO Companies of 2020 appeared first on Neil Patel.

Original content source: https://neilpatel.com/blog/technical-seo-companies/ via https://neilpatel.com

See the original post, The 4 Best Technical SEO Companies of 2020 that is shared from https://imtrainingparadise.weebly.com/home/the-4-best-technical-seo-companies-of-2020 via https://imtrainingparadise.weebly.com/home

[jjpocketbook]

The 4 Best Technical SEO Companies of 2020

No matter how great the content on your website is, your hard work could amount to nothing without proper technical SEO. 

Technical SEO gives your site structure, makes it super easy for search engine bots to crawl and index, and helps Google understand what each page is about. 

URL structuring, robots.txt, redirect codes, canonical tags, .htaccess files, load time, and many others. It all matters.

Do all those things sound unfamiliar to you? No? 

Well, you don’t need to.

Tons of companies already know this stuff and it’s really easy to work with them.

That’s where this guide comes in. 

Our team at Neil Patel Digital researched, reviewed, and listed the top technical SEO companies on four criteria: 

Outstanding customer reviews.

Awards, impressive clientele, and a long history of delivering stellar technical SEO work.

Thought-leadership—consistently publishing of insightful articles and trends on the topic.

A strong reputation amongst other SEO professionals.

From these criteria, we found technical SEO companies you can trust and what they’re good for:

The 4 Top Technical SEO Companies in The World

Neil Patel Digital – Best for Technical Content Structuring

Webris – Best for Technical SEO Audits

Salt.agency  – Best for Enterprise Technical SEO

Orainti – Best for Ecommerce Brands

Without further ado, let’s dive into what makes us trust and bet our reputation on these companies. 

1. Neil Patel Digital – Best For Technical Content Structuring

It’s been touted over and again that content is king. While there’s truth in this, what most people never take into consideration is content structuring. 

Neil Patel Digital is the go-to SEO company for excellent content structuring.

Well, don’t take my word for it. Let me show you why. 

From our years of extensive search engine optimization experience, we found that for content marketing to work and power long-term SEO strategy, it must have the right structure. 

This is a key piece of our comprehensive SEO program.

And what have we to show for doing this, you ask? 

The result of doing this speaks for itself: 

Over 3 million visitors per month on this blog. All built from scratch.

Content was a huge part of this but the site wouldn’t be nearly as large without the right structure and technical SEO.

You can get access to this vast technical SEO expertise by working with the Neil Patel Digital team.

Today, we’ve developed a content marketing program with content structuring (in the form of content clusters) to help clients get technical SEO right from day one.

2. Webris – Best for Technical SEO Audits

Almost all great endeavors begin with taking in-depth audits of what’s already existing. 

Technical SEO is no exception. 

You won’t achieve much in your effort to optimize your site for search engine bots’ crawling and indexing without first doing a proper audit of your site’s structure. 

And Webris is the company we recommend for technical SEO audits.

If you a do quick Google search for “technical SEO audit,” you’ll find this excellent content piece by Webris:

Ranking on Google’s top spot for this search term is another way of saying that earned its stripes on this list. 

No company can earn that by accident. 

This proves that Webris walks the talk when it comes to technical SEO audits and is a reliable option if you’re just getting started. 

Founded by Ryan Stewart, the core strengths of Webris is technical SEO audits and conversion-focused UX. This company boasts of an incredibly talented team of advanced technical SEO consultants. 

Major brands like Shopify and Accenture trust Webris and have worked with them.

3. Salt.agency – Best for Enterprise Technical SEO

Salt.agency prides itself on “Technical Excellence” and that’s for a good reason. This company breathes technical SEO before anything else:

Massive enterprise sites can have all sort of crazy technical problems.

If you’re running one of these sites, you need a team that’s worked with that type of complexity before.

In this case, Salt.agency is the best option.

With offices in Boston, Leeds, and London, Salt.agency’s clients include Cloudflare, Hartley Botanic, Brex, Travel Supermarket, and many others.

4. Orainti – Best for Ecommerce Brands

Orainti specializes in providing technical and strategic SEO services for brands in competitive industries. 

This company approaches digital marketing and search engine optimization with a technical mindset, which justifies its inclusion in this highly-vetted list. 

And they work mostly with ecommerce brands selling internationally. 

International ecommerce businesses  have tons of unique challenges like dealing with multilingual sites, getting product and category pages ranked properly, and avoiding duplicate content. 

Orainti comes highly recommended for this.

Aleyda Solis is the Founder of Orainti. She is a veteran SEO practitioner, speaker, and author who has earned recognition and awards for her technical SEO expertise by organizations such as Forbes and European Search Awards. 

Orainti boasts an impressive portfolio of top brands, including Zillow, Under Armour, Sage, Eventbrite, and others.

5 Characteristics That Make a Great Technical SEO Company

What separates the good technical SEO shops from the great ones? What would you specifically look for when choosing someone to work with? 

Here’s what I look for.

1. A Complete Implementation Process that Includes Technical SEO

Technical SEO brings structure to your site. It helps search engine bots crawl, index, and rank your website correctly, which is essential for driving traffic. 

Also, it helps to boost your site’s load time. 

However, this doesn’t mean that once you have an excellent technical SEO, everything search engine optimization will fall in place automatically. 

The best technical SEO companies have a complete SEO program including manual site review, technical SEO implementation, content strategy, and others.

If you’re really good at SEO already and just need a quick SEO audit to double check everything, you could get value at working with a specialist. But for everyone else, I recommend working with someone that understands the complete SEO strategy. It’s the only way to build a site with tons of traffic.

2. Thought leadership

It takes lots of experimentation to implement technical SEO strategies that move the needle. Companies that embark on this kind of excruciating work always like to document their experience and findings.

Working with SEO thought leaders increases the odds of a successful project.

After all, if someone can successfully teach technical SEO, they can also help your business directly.

Publishing cutting-edge content about technical SEO is a great sign that they’ll deliver amazing results. 

3. An Impressive Client Portfolio

An excellent way to see if the expertise and processes used by a technical SEO company works is by looking at its client portfolio.

There is nuance here.

Having a ton of major brands is great. But that doesn’t mean that you can get help with your exact situation.

Ideally, the technical SEO company has worked with similar companies like your own.

4. Real Life Results

The nice thing about technical SEO is that it’s extremely practical. Technical problems come up that tanks traffic. Then technical SEO experts fix those problems.

It’s cut and dry.

Any great technical SEO company should have plenty of case studies where they turned around a site after it got hit. The more obscure the technical problem, the more likely they’ll be able to find weird problems on your own site.

Sometimes, these case studies are published on their site. But a lot of companies don’t like sharing the best stories. So ask their team as you talk to them. They should be able to give you plenty of examples during a call.

5. A Diversified Team

Covering every last technical SEO requirement is way too big of a task for a single person. You’ll need a fully-staffed team to do it all. Especially on major sites.

Go through the company’s team pages and LinkedIn employees, then look for lots of depth and expertise across the entire team.

What to Expect from a Great Technical SEO Company 

If you’re like most people who only realize the need for technical SEO late on, you’ll probably be wondering what you should expect from one. 

The most significant things to expect are what follows. 

1. A discovery session

After you reach out to a technical SEO company, they’ll want to get on a call to understand what you’re looking for. 

It’s the only way to understand the goals that you have for your site.

If a technical SEO company wants to jump straight into an audit without even getting on the phone, it’s a sign they’re running an “audit mill” and aren’t going to spend much time on your project.

Find a company that wants to go really deep and understand the full picture.

2. A one-time audit proposal

Most technically SEO companies will perform a one-time audit for a flat fee. 

Since this is a standard part of their practice, they can usually jump into this right away.

Assuming their fee works with your budget, you could have someone get started within a week. That’s how easy it is to get going.

Before starting the audit, ask them for everything that they’ll check. It should include everything like canonical problems, indexing issues, duplicate content, other Google Search Console errors, everything.

If the list doesn’t feel extremely comprehensive, get a few quotes from other companies.

3. Completing the audit

Once you’ve agreed to move forward with an audit, the company will get started.

These usually take a few weeks to complete, depending on the size of your site.

Of course, you’ll need to give them access to your Google Analytics, Google Search Console, WordPress account, and possibly your web host.

During the audit, there shouldn’t be much work for you or your team. The company performing the audit may have questions but they can do the vast majority of the work on their own.

4. Implementation proposal

Most technical SEO audits only include the discovery of site issues. The project doesn’t usually include the work that’s required to fix any problems.

This is because most problems don’t have easy fixes.

For example, if your site has terrible site speed that’s impacting your rankings, you’ll need to do a ton of front-end work in order to fix it. That will also involve your marketing team and possibly other agencies.

So once the audit is complete, expect to see a proposal that includes implementing any solutions.

Something to watch for here: a great technical SEO company will know the limits of it’s expertise. When they find problems outside their capabilities, they’ll tell you and advise you to work with someone else on fixing them. Site rebuilds and content marketing are good examples of this.

If a technical SEO agency tells you that it can fix every single problem, double check and make sure they truly have real expertise in those areas.

Should I take Technical SEO Seriously?

Yes!

Technical SEO is like the frame of your house. Only with good bones can your content and marketing drive traffic to your site. 

But, as things add up, and you have hundreds or thousands of pages on your site, something is going to break. 

Search engines have a harder time crawling your site, content isn’t indexed, and your site speed slows way down.

Even if you start with a great foundation, you need a healthy rebuild every few years.

If you haven’t done a deep technical SEO audit recently, now’s the time.

The post The 4 Best Technical SEO Companies of 2020 appeared first on Neil Patel.

Original content source: https://neilpatel.com/blog/technical-seo-companies/ via https://neilpatel.com

The original post, The 4 Best Technical SEO Companies of 2020, has been shared from https://imtrainingparadise.wordpress.com/2020/11/13/the-4-best-technical-seo-companies-of-2020/ via https://imtrainingparadise.wordpress.com