Pierre-Andre Cornillon, Arnaud Guyader, Francois Husson, Nicolas Jegou, Julie Josse, Maela Kloareg, ric Matzner-Lober, Laurent Rouvière

Section 4.2 on the apply family of functions and related functions for matrices, arrays, and data frames is by far the most friendly and helpful introduction to the subject that I have seen. ... All datasets, along with the R-code in the book, are available on the website for the text. ... If you are not a trained programmer but you aspire to write code that is efficient and perhaps, from time to time, clever, then this book is a fine place for you to start learning R. -Homer S. White, MAA Reviews, January 2013 [T]he book is accessible for statisticians of all levels and areas of expertise as well as for novice and advanced R users. ... I recommend it for anyone who wants to learn about the why and how of the most commonly employed statistical methods and their extensions. -Irina Kukuyeva, Journal of Statistical Software, Vol. 51, November 2012

• An Overview of R: Main Concepts. Preparing Data. R Graphics. Making Programs with R. Statistical Methods: Introduction to the Statistical Methods. A Quick Start with RHypothesis Test. Regression. Analysis of Variance and Covariance. ClassificationExploratory Multivariate Analysis. Clustering. Appendix.