Product Description A Proven Guide for Easily Using R to Effectively Analyze Data Like its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references. New to the Second Edition New chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distribution New examples and additional exercises in several chapters A new version of the HSAUR package (HSAUR2), which is available from CRAN This edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data. Review I find the book by Everitt and Hothorn quite pleasant and bound to fit its purpose. The layout and presentation [are] nice. It should appeal to all readers as it contains a wealth of information about the use of R for statistical analysis. Included seasoned R users: When reading the first chapters, I found myself scribbling small lightbulbs in the margin to point out features of R I was not aware of. In addition, the book is quite handy for a crash introduction to statistics for (well-enough motivated) nonstatisticians.?International Statistical Review (2011), 79â¦ an extensive selection of real data analyzed with [R] â¦ Viewed as a collection of worked examples, this book has much to recommend it. Each chapter addresses a specific technique. â¦ the examples provide a wide variety of partial analyses and the datasets cover a diversity of fields of study. â¦ This handbook is unusually free of the sort of errors spell checkers do not find. â¦ ? MAA Reviews, April 2011 Praise for the First Editionâ¦Brian Everitt has joined forces with a recognized expert who displays an impressive command of this powerful environment â¦ Much is to be learned in the small details that make this text interesting even for experienced users. â¦ Special attention is given to graphical methods â¦ ?Journal of Applied Statistics, May 2007 Useful examples are presented to assist understanding. â¦ Everitt and Hothorn have written an excellent tutorial on using R to analyze data using a wide range of standard statistical methods. â¦ I highly recommend the text for anyone learning R and who want to use it for the sophisticated analysis of data.?Joseph M. Hilbe, Journal of Statistical Software, Vol. 16, August 2006 â¦a useful, compact introduction.?Biometrics, December 2006 â¦ This book, using analyses of real sets of data, takes the reader through many of the standard forms of statistical methodology using R. â¦ a very valuable reference. â¦The book is particularly good at highlighting the graphical capabilities of the language. â¦?P. Marriott, ISI Short Book Reviews About the Author Brian S. Everitt is Professor Emeritus at Kingâs College, University of London. Torsten Hothorn is Professor of Biostatistics in the Institut fÃ¼r Statistik at Ludwig-Maximilians-UniversitÃ¤t MÃ¼nchen.