The Book of R: A First Course in Programming and Statistics
- Length: 832 pages
- Edition: 1
- Language: English
- Publisher: No Starch Press
- Publication Date: 2016-07-23
- ISBN-10: 1593276516
- ISBN-13: 9781593276515
- Sales Rank: #34758 (See Top 100 Books)
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.
Table of Contents
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 Visualization
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