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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.
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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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