Includes bibliographical references (pages 761-765) and index.

pt. I. The language. Getting started -- Numerics, arithmetic, assignment, and vectors -- Matrices and arrays -- Non-numeric values -- Lists and data frames -- Special values, classes, and coercion -- Basic plotting -- Reading and writing files -- pt. II. Programming. Calling functions -- Conditions and loops -- Writing functions -- Exceptions, timings, and visibility -- pt. III. Statistics and probability. Elementary statistics -- Basic data visualization -- Probability -- Common probability distributions -- pt. IV. Statistical testing and modeling. Sampling distributions and confidence -- Hypothesis testing -- Analysis of variance -- Simple linear regression -- Multiple linear regression -- Linear model selection and diagnostics -- pt. V. Advanced graphics. Advanced plot customization -- Going further with the grammar of graphics -- Defining colors and plotting in higher dimensions -- Interactive 3D plots - Appendix A. Installing R and contributed packages -- Appendix B. Working with RStudio. "A beginner's guide to programming with R, the statistical programming language. Covers key programming techniques like manipulating data structures, reading data from a file, and writing functions. Introduces statistics topics like probability distributions, hypothesis testing, regression analysis, and statistical plots. Includes exercises throughout each chapter"-- "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 using R effectively for statistical analysis. 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 statistical tests and modeling. You'll even learn how to create impressive data visualizations with R's basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) 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 data sets; how to draw valid and useful conclusions from your data; [and] how to create publication-quality graphics of your results. 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." -- Publisher's description