The Book of R

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 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.

Tilman M. Davies is a senior lecturer at the University of Otago in New Zealand, where he teaches statistics and R at all university levels. He has been programming in R for 10 years and uses it in all of his courses.

Preface
PART 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 Files
PART II PROGRAMMING
9 Calling Functions
10 Conditions and Loops
11 Writing Functions
12 Exceptions, Timings, and Visibility
PART III STATISTICS AND PROBABILITY
13 Elementary Statistics
14 Basic Data Visualization
15 Probability
16 Common Probability Distributions
PART 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 Diagnostics
PART 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 Plots
APPENDICES
A Installing R and Contributed Packages
B Working with RStudio
Bibliography