Synopsis
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.
"synopsis" may belong to another edition of this title.
About the Author
Brian S. Everitt is Professor Emeritus at King’s College, University of London.
Torsten Hothorn is Professor of Biostatistics in the Institut für Statistik at Ludwig-Maximilians-Universität München.
"About this title" may belong to another edition of this title.
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A Handbook of Statistical Analyses Using R, Second Edition
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