This long-awaited second edition folds years of updates into its beginner-friendly lessons on using R for data and statistical analysis.
This long-awaited second edition folds years of updates into its beginner-friendly lessons on using R for data and statistical analysis.
The 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 writing programs in R.
You'll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing tests and modeling. You'll even learn how to create impressive data visualizations with R's graphics tools and contributed packages, like ggplot2, ggvis, and rgl.
Dozens of hands-on exercises take you from theory to practice as you learn-
The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling and how to execute them in R How to access R's thousands of functions, libraries, and datasets How to draw valid and useful conclusions from your data and create publication-quality graphics of your results
The Book of R brings both statistics and R to life. With clear explanations, practical examples, and hands-on exercises, this book opens the door to the evolving world of data analysis.
New to this edition- The entire book has been revised and expanded, with nearly 100 pages of new content and exercises. You'll find greater coverage of data plots and R graphics, guidance on using pipes to string together commands, and new ways to read and write external files, among many other lessons.
By:
Tilman M. Davies
Imprint: No Starch Press,US
Country of Publication: United States
Dimensions:
Height: 234mm,
Width: 177mm,
Weight: 369g
ISBN: 9781718503687
ISBN 10: 1718503687
Pages: 908
Publication Date: 25 November 2025
Audience:
General/trade
,
ELT Advanced
Format: Paperback
Publisher's Status: Forthcoming
Preface Acknowledgments Introduction PART I: THE LANGUAGE Chapter 1: Getting Started Chapter 2: Numerics, Arithmetic, Assignment, and Vectors Chapter 3: Matrices and Arrays Chapter 4: Non-Numeric Values Chapter 5: Lists and Data Frames Chapter 6: Special Values, Classes, and Coercion Chapter 7: Basic Plotting Chapter 8: Reading and Writing Files PART II: PROGRAMMING Chapter 9: Calling Functions Chapter 10: Conditions and Loops Chapter 11: Writing Functions Chapter 12: Exceptions, Timings, and Visibility PART III: STATISTICS AND PROBABILITY Chapter 13: Elementary Statistics Chapter 14: Basic Data Visualizations Chapter 15: Probability Chapter 16: Common Probability Distributions PART IV: STATISTICAL TESTING AND MODELING Chapter 17: Sampling Distributions and Confidence Chapter 18: Hypothesis Testing Chapter 19: Analysis of Variance Chapter 20: Simple Linear Regression Chapter 21: Multiple Linear Regression Chapter 22: Linear Model Selection and Diagnostics PART V: ADVANCED GRAPHICS Chapter 23: Advanced Plot Customization Chapter 24: Going Further with the Grammar of Graphics Chapter 25: Defining Colors and Plotting in Higher Dimensions Chapter 26: Interactive 3D Plots Appendix A: Installing R and Contributed Packages Appendix B: Working with RStudio Reference List
Tilman M. Davies is an academic at the Department of Mathematics and Statistics at the University of Otago in New Zealand, where he teaches statistics at all university levels. He has been programming in R since the early 2000s and uses it in all of his courses. Davies has received multiple significant research grants for his methodological work in spatial statistics and in 2024 received the Littlejohn Award, the premier research award of the New Zealand Statistical Association.
Reviews for The Book of R, 2nd Edition: A First Course in Programming and Statistics
“A game changer.” —Kirk Borne, principal data scientist at Booz Allen Hamilton
