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.
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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 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 John Verzani - Chapman & Hall/CRC
A self-contained treatment of statistical topics and the intricacies of the R software. The book focuses on exploratory data analysis, includes chapters on simulation and linear models. It lays the foundation for further study and development using R.
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.