An Introduction to Statistical Learning: With Applications in R

Renting vs. Buying This Textbook

Renting is usually cheapest if you only need the book for one term: you return it with a free prepaid label when the term ends. Buying used can beat renting when the sell-back price is high, so compare the sell-back price with the rental price before you decide. An eTextbook arrives instantly but usually expires. Rentals and used copies rarely include working access codes.

Always match the ISBN on your syllabus (9781461471370) before you order; different editions have different ISBNs.

About This Book

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in…