Manga Guide to Regression Analysis

Shin Takahashi attended Kyushu University, where he graduated with a master's degree in information technology. Having previously worked both as a data analyst and an instructor, he is now an author specializing in technical books. He is the author of The Manga Guide to Statistics and The Manga Guide to Linear Algebra (No Starch Press).

“Like Larry Gonick’s Cartoon Guide to Statistics, The Manga Guide to Regression Analysis similarly helps students grasp the meaning of R-squared, correlation coefficients, and null hypotheses—terms that have proved to be the bane of many students’ college careers.”—Foreword Reviews“It’s a great little book if you need to know regression, without doing a full-on mathematical course.”—Cosmos Magazine“The Manga Guide to Regression Analysis makes learning about complex math equations sound much less like a chore and more like a fun afternoon.”—GeekMom“The manga sections nail down all the big concepts in an easy-to-read way so that the reader is better prepared for the traditional sections that follow. Don't let the manga brand fool you; it's a legitimate way to learn the material.”—Otaku USA Magazine“Each chapter begins with an overview of the problem at hand, a very 'high-level' discussion of the proposed regression technique, a clear outline of the necessary steps involved, and then the complete regression procedure is worked out. . . . Students will benefit greatly from this.”—The Mathematical Association of America“The use of manga might lull you into thinking that it lacks depth, but autocorrelation, logistic regression, and even the Mahalanobis difference are covered so it goes well beneath the surface.”—Dr. Catey Bunce, Lead Statistician at Moorfields Eye Hospital NHS Foundation Trust“Another fantastic Manga Guide book. Everyone learns differently, and this method of using an example tied to characters in a logical (business) situation makes learning the basics of regression analysis fun and relatively easy.”—Sequential Tart“Reading this book might be a nice prelude to diving into a statistical programming environment like R, since topics like ANOVA, confidence intervals, residuals, R-squared, multicollinearity etc. will make a lot more sense. As an added bonus, the book covers binomial logistic regression which is another popular supervised learning method designed to predict probabilities whether or not something will happen.”—insideBIGDATA“Never have I seen such an adorable way to learn higher-level mathematical techniques...The characters are fun and lively. It’s encouraging to see someone so eager to learn more about variance analysis and confidence intervals.”—Comics Worth Reading"A detailed, in-depth educational tool ideal for classroom use or self-study! Highly recommended, especially for high school, college, and public library mathematics collections." —Midwest Book Review

• Prologue: More Tea?Chapter 1: A Refreshing Glass of MathChapter 2: Regression AnalysisChapter 3: Multiple Linear Regression AnalysisChapter 4: Logistic Regression Analysis