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### Errors of Regression Models

###### One Stat to Rule Them All

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## Now With 2 Free Bonuses!

You can now get the following FREE bonuses with this book:

The Future of Statistics

• An anthology written with the contributions of some of the most prominent statisticians, data analysts and Data Scientists in the world to help you take the next steps in your Data Ninja journey!

Machine Learning Model Assessments - The Big Picture

• An Ultra Hi-Def poster created to help you understand which statistics to use in every situation!

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Sometimes, learning about statistics can be a bit like peering into a crystal ball. You think you’ve got it, only to read one more article/paper/blog, and suddenly it’s as clear as mud again, and you’re further away from the answer than when you first started.

Choosing the correct statistic to use in any given situation can seem like a daunting task at times. When there are numerous possible statistical calculations you can do with your data, there is not usually one correct answer – in most cases there is a spectrum of approaches, some of which are more appropriate than others.

In Errors of Regression Models you’ll learn how to choose the most appropriate statistics to measure the accuracy of your regression-based prediction model.

You’ll discover that there is a family of related statistics, each member of which has their own set of dedicated fans.

Nevertheless, in this case, there is one correct statistic to use, while all the other measures – while useful in their own way – give only partial answers as to how to select the most accurate predictive model.

Each of these family members will be introduced, and Errors of Regression Models will explain all their advantages and disadvantages, and show you precisely how to calculate and interpret all of them. Finally, Errors of Regression Models will explain exactly why one particular family member is The Daddy!

Written in plain English with no technical jargon, Errors of Regression Models is perfect for beginners!

Discover how to measure the accuracy of your regression models quickly and effectively. Get this book, TODAY!

• ### Categories

• Artificial Intelligence
• Data Science
• Machine Learning
• Sciences
• ### Feedback

Email the Author(s)

Lee Baker

Lee Baker is an award-winning software creator with a passion for turning data into a story.

A proud Yorkshireman, he now lives by the sparkling shores of the East Coast of Scotland.

Physicist, statistician and programmer, child of the flower-power psychedelic ‘60s, it’s amazing he turned out so normal!

Turning his back on a promising academic career to do something more satisfying, as the CEO and co-founder of Chi-Squared Innovations he now works double the hours for half the pay and 10 times the stress - but 100 times the fun!

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Introduction

The Misunderstood: Errors, Residuals, Deviations

The Black Sheep of The Family: The R2 Value

The Tearaway: Variance of Residuals

The Good Twin: Mean Absolute Error

The Evil Twin: Mean Error

The Daddy: Root Mean Square Error

Jeez, That’s One Dysfunctional Family!

Summary – One Stat to Rule Them All

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