A First Course in Statistical Programming with R (3^rd Ed., Revised edition)

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box?Muller and Metropolis?Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most computing languages and techniques used to develop more complex projects. Solutions, datasets, and any errata are available from www.statprogr.science. Worked examples - from real applications - hundreds of exercises, and downloadable code, datasets, and solutions make a complete package for anyone working in or learning practical data science.

1. Getting Started; 2. Introduction to the R Language; 3. Programming Statistical Graphics; 4. Programming with R; 5. Complex Programming in the Tidyverse; 6. Simulation; 7. Computational Linear Algebra; 8. Numerical Optimization; A. Review of Random Variables and Distributions; B. Base Graphics Details; Index.

W. John Braun is Professor of Statistics at UBC's Okanagan campus. His research interests are in the modeling of environmental phenomena, such as wildfire, as well as statistical education, particularly as it relates to the R programming language.
Duncan J. Murdoch is a Professor Emeritus and was a member of the R Core Team of developers and co-president of the R Foundation. He is one of the developers of the rgl package for 3D visualization in R, and has also developed numerous other R packages.