Errors of Regression Models: One Stat to Rule Them All (Bite-Size Machine Learning, #1)

When two regression models make predictions, how do you decide which one is more accurate? Errors of Regression Models tackles that practical question by sorting through the statistics commonly used to assess predictive performance—and explaining why each measure tells only part of the story.

Lee Baker keeps the focus on interpretation as well as calculation. The result is a short, plain-language introduction for readers who want to understand the numbers behind regression-model comparisons without losing sight of what those numbers actually mean.

Meet the measures behind model accuracy

The book begins by untangling three easily confused terms: errors, residuals, and deviations. From there, it examines a family of measures used to evaluate regression predictions, including R², variance of residuals, mean absolute error, mean error, and root mean square error (RMSE).

Understand what each statistic can—and cannot—tell you

Rather than treating every measure as interchangeable, Baker considers the strengths and drawbacks of each one. That distinction matters: a metric can be useful while still offering only a partial answer to the question of which predictive model is performing better.

• Clarifies terminology used when discussing predictions and observed values.
• Introduces several common measures of regression-model accuracy.
• Explains how to calculate and interpret the measures covered.
• Compares their advantages and limitations, with particular attention to RMSE.

A readable starting point for regression evaluation

Part of the Bite-Size Machine Learning series, this book may suit newcomers to model assessment as well as analysts and data-science learners looking to refresh their understanding of familiar statistics. Its central theme is useful well beyond any one formula: choosing a measure means understanding the question it answers.

If regression metrics have ever seemed like a jumble of competing answers, Baker’s guide offers a focused way to make sense of the differences.