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.
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
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