R for Statistics

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