Cornillon P.-A., Guyader A., Husson F., Jegou N., Josse J., Kloareg M., Matzner-Lober E., Rouvière L. R for Statistics

Boca Raton: Chapman and Hall/CRC, 2012. — 312 p. — ISBN: 978-1-4398-8146-0.Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples.
Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R.
Focusing on the R software, the first section covers:
Basic elements of the R software and data processing Clear, concise visualization of results, using simple and complex graphs Programming basics: pre-defined and user-created functions
The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including:
Regression methods
Analyses of variance and covariance
Classification methods
Exploratory multivariate analysis
Clustering methods
Hypothesis tests
After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.
Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat