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-How to create publication-quality graphics of your resultsCombining 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.

PrefacePART I THE LANGUAGE 1 Getting Started 2 Numerics, Arithmetic, Assignment, and Vectors 3 Matrices and Arrays 4 Non-numeric Values 5 Lists and Data Frames 6 Special Values, Classes, and Coercion 7 Basic Plotting 8 Reading and Writing FilesPART II PROGRAMMING 9 Calling Functions 10 Conditions and Loops 11 Writing Functions 12 Exceptions, Timings, and VisibilityPART III STATISTICS AND PROBABILITY 13 Elementary Statistics 14 Basic Data Visualization 15 Probability 16 Common Probability DistributionsPART IV STATISTICAL TESTING AND MODELING 17 Sampling Distributions and Confidence 18 Hypothesis Testing 19 Analysis of Variance 20 Simple Linear Regression 21 Multiple Linear Regression 22 Linear Model Selection and DiagnosticsPART V ADVANCED GRAPHICS 23 Advanced Plot Customization 24 Going Further with the Grammar of Graphics 25 Defining Colors and Plotting in Higher Dimensions 26 Interactive 3D PlotsAPPENDICES A Installing R and Contributed Packages B Working with RStudioBibliography