The 15 Best R Programming Books Based on Real User Reviews


The Best R Programming Books

Our editors have compiled this directory of the best R programming books based on Amazon user reviews, rating, and ability to add business value.

There are loads of free resources available online (such as Solutions Review’s Data Analytics and Business Intelligence Software Buyer’s Guide, Visual Comparison Matrix, and best practices section) and those are great, but sometimes it’s best to do things the old fashioned way. There are few resources that can match the in-depth, comprehensive detail of one of the best R programming books.

The editors at Solutions Review have done much of the work for you, curating this comprehensive directory of the best R programming books on Amazon. Titles have been selected based on the total number and quality of reader user reviews and ability to add business value. Each of the books listed in this compilation have met a minimum criteria of 100 reviews and a 4-star-or-better ranking.

Below you will find a library of titles from recognized industry analysts, experienced practitioners, and subject matter experts spanning the depths of R for data science all the way to R for machine learning and other use cases. This directory includes publications for practitioners of all skill levels.

The Best R Programming Books

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

OUR TAKE: The most popular R-focused book on Amazon touts a nearly perfect rating of 4.8 stars, this title is targeted at statisticians and non-statisticians alike and was written by the authors of The Elements of Statistical Learning.

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)“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. 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.”

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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

OUR TAKE: This title is the number-one seller in Amazon’s Mathematical & Statistical Software category. Author Hadley Wickham is an Assistant Professor and the Dobelman FamilyJunior Chair in Statistics at Rice University.

R for Data Science: Import, Tidy, Transform, Visualize, and Model Data“Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details.”

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Discovering Statistics Using R

OUR TAKE: This book received rave reviews from some of the foremost experts in the field. Author Andy Field is Professor of Quantitative Methods at the University of Sussex and has published more than 150 research papers, book chapters and full-length titles.

Discovering Statistics Using R“The R version of Andy Field′s hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R. Like its sister textbook, Discovering Statistics Using R is written in an irreverent style and follows the same ground breaking structure and pedagogical approach. The core material is enhanced by a cast of characters to help the reader on their way, hundreds of examples, self assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.”

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462

R For Dummies

OUR TAKE: The second edition of this popular text will teach you how to reshape and manipulate data, merge data sets, split and combine data, and perform calculations on vectors and arrays.

R For Dummies“R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. RFor Dummies provides a quick and painless way to master all the R you’ll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel.”

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The Art of R Programming: A Tour of Statistical Software Design

OUR TAKE: Author Norman Matloff is a Professor of Computer Science at the University of California, Davis and the creator of several popular software packages and web tutorials on computer graphics.

The Art of R Programming: A Tour of Statistical Software Design“The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you’ll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. Whether you’re designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.”

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258

Statistical Analysis with R For Dummies

OUR TAKE: This easy-to-follow guide focuses on the foundational statistical concepts that R addresses, as well as step-by-step guidance that shows you how to implement them in the R programming language.

Statistical Analysis with R For Dummies“People are becoming more aware of R every day as major institutions are adopting it as a standard. Part of its appeal is that it’s a free tool that’s taking the place of costly statistical software packages that sometimes take an inordinate amount of time to learn. Plus, R enables a user to carry out complex statistical analyses by simply entering a few commands, making sophisticated analyses available and understandable to a wide audience. Statistical Analysis with R For Dummies enables you to perform these analyses and to fully understand their implications and results.

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213

The Book of R: A First Course in Programming and Statistics

OUR TAKE: The Book of R is a gentle yet informative introduction to the statistical software environment R. It is for anyone interested in programming, statistics, and data analysis, and is especially well-suited for students and instructors of statistics courses.

The Book of R: A First Course in Programming and StatisticsThe Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.”

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211

R in Action: Data Analysis and Graphics with R

OUR TAKE: This book teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats.

R in Action: Data Analysis and Graphics with RR in Action, presents both the R language and the examples that make it so useful for business developers. Focusing on practical solutions, the book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods. You’ll also master R’s extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on time series analysis, cluster analysis, and classification methodologies, including decision trees, random forests, and support vector machines.

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198

Machine Learning with R: Expert techniques for predictive modeling

OUR TAKE: The new 3rd edition updates the classic R data science book to R 3.6 with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning.

Machine Learning with R: Expert techniques for predictive modeling“Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to…



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