The Art of R Programming
by Norman Matloff
Publisher: UC Davis 2009
Number of pages: 193
This book is for those who wish to write code in R, as opposed to those who use R mainly for a sequence of separate, discrete statistical operations. The reader's level of programming background may range from professional to novice.
Download or read it online for free here:
by W. N. Venables, D. M. Smith - Network Theory
Comprehensive introduction to R, a software package for statistical computing and graphics. R supports a wide range of statistical techniques, and is easily extensible via user-defined functions, or using modules written in C, C++ or Fortran.
by J H Maindonald - Australian National University
These notes are designed to allow individuals who have a basic grounding in statistical methodology to work through examples that demonstrate the use of R for a range of types of data manipulation, graphical presentation and statistical analysis.
by Roger D. Peng - Leanpub
This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies.
by Colin Gillespie, Robin Lovelace - O'Reilly
The book is about increasing the amount of work you can do with R in a given amount of time. It's about both computational and programmer efficiency. It's for anyone who uses R and who wants to make their use of R more reproducible and faster.