A Handbook of Statistical Analyses Using R

by Torsten Hothorn, Brian S. Everitt

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.

Genres: Nonfiction

376 pages, Paperback

First published February 17, 2006

Reviews

[Darin]

This is not your standard statistics book nor your standard book on R. It is best for people who already know something about each. Each chapter is devoted to different statistical topics, but in each the author analyzes a different data set showing each step as it would be implemented using R.

[Quazirfan · Rating 1 out of 5]

I've found the book lacking direction. The author tried to cover both the mathematical and the practical side and failed to do both in my experience.