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A Handbook of Statistical Analyses Using R, Second Edition [Paperback]

Brian S. Everitt (Author), Torsten Hothorn (Author)
4.0 out of 5 stars  See all reviews (5 customer reviews)

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Book Description

July 20, 2009 1420079336 978-1420079333 2

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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Editorial Reviews

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), 79

… an extensive selection of real data analyzed with [R] … Viewed as a collection of worked examples, this book has much to recommend it. Each chapter addresses a specific technique. … the examples provide a wide variety of partial analyses and the datasets cover a diversity of fields of study. … This handbook is unusually free of the sort of errors spell checkers do not find. …
MAA Reviews, April 2011

Praise for the First Edition
…Brian Everitt has joined forces with a recognized expert who displays an impressive command of this powerful environment … Much is to be learned in the small details that make this text interesting even for experienced users. … Special attention is given to graphical methods …
Journal of Applied Statistics, May 2007

Useful examples are presented to assist understanding. … Everitt and Hothorn have written an excellent tutorial on using R to analyze data using a wide range of standard statistical methods. … 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

…a useful, compact introduction.
Biometrics, December 2006

… This book, using analyses of real sets of data, takes the reader through many of the standard forms of statistical methodology using R. … a very valuable reference. …The book is particularly good at highlighting the graphical capabilities of the language. …
—P. Marriott, ISI Short Book Reviews

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.


Product Details

  • Paperback: 376 pages
  • Publisher: Chapman and Hall/CRC; 2 edition (July 20, 2009)
  • Language: English
  • ISBN-10: 1420079336
  • ISBN-13: 978-1420079333
  • Product Dimensions: 9.2 x 5.9 x 1 inches
  • Shipping Weight: 1.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #243,137 in Books (See Top 100 in Books)

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42 of 42 people found the following review helpful:
5.0 out of 5 stars One of the best books on R, January 9, 2010
This review is from: A Handbook of Statistical Analyses Using R, Second Edition (Paperback)
I have never formally studied any statistical programming language or taken any advanced statistics courses, but I have been self-teaching myself statistics and R. In a nutshell, this book helped me to improve my R skills substantially. Initially I was using online R documentation alone, and the learning went somewhat slowly. This was the first book that I actually purchased on R, and it really is useful. This is fundamentally a book on the use of R rather than on statistical theory.

The book starts with a couple of brief chapters on the R language and basic statistics, but most of the book is concerned with more advanced statistical topics such as principal component analysis, meta-analysis, clustering, and other topics. Each chapter is devoted to a particular statistical technique with an explanation of why you would use that method and brief mathematical background. However, the chapters are mostly devoted to using R to solve example problems. The author uses good examples with educational R code. He does not simply state that a particular command can do something. Rather, he starts from scratch with each example, first by showing the data, then showing the R code to clean it up if needed. He then shows the R code to perform the statistical analysis diagnostics on the solutions.

If you know absolutely no R and no statistics, then this book will not be much use. However, if you know a little R and have grasp of the fundamental principles of statistics (basic probability, parametric vs non-parametric methods, chi-square, t-test, etc...) then this book can improve your R skills tremendously.

A word of caution, however, is that I would not use this book (or any R book for that matter) alone. Additionally, if you do not know the basic logic behind the advanced statistical methods in this book, then you may find that you have to go elsewhere to learn that material. I still go to the internet constantly and when necessary refer to other statistical texts unrelated to R (including one written by Everitt).
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6 of 9 people found the following review helpful:
5.0 out of 5 stars Second Edition is even better!, December 26, 2009
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This review is from: A Handbook of Statistical Analyses Using R, Second Edition (Paperback)
I had used the 1st edition and I find the 2nd edition even better. It is a useful book for Statisticians who like to work in R. It introduces the reader to most of the useful advanced techniques.
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1 of 3 people found the following review helpful:
5.0 out of 5 stars Great book to get started., February 6, 2011
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This review is from: A Handbook of Statistical Analyses Using R, Second Edition (Paperback)
Great book for the advanced or the beginner. All the examples worked and were easy to use in other scenario.
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