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A Handbook of Statistical Analyses Using R

TextbookHandbook / ManualSPECIAL OFFER

By: Torsten Hothorn(Author), Brian S Everitt(Author)

421 pages, 153 b/w illustrations, 78 tables

Apple Academic Press

Paperback | Jul 2014 | Edition: 3 | #212156 | ISBN-13: 9781482204582
Availability: In stock
Clearance price: £31.19 £47.99 (Save £16.80) $41/€35 approx

About this book

Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.

New to the Third Edition
- Three new chapters on quantile regression, missing values, and Bayesian inference
- Extra material in the logistic regression chapter that describes a regression model for ordered categorical response variables
- Additional exercises
- More detailed explanations of R code
- New section in each chapter summarizing the results of the analyses
- Updated version of the HSAUR package (HSAUR3), which includes some slides that can be used in introductory statistics courses

Whether you're a data analyst, scientist, or student, A Handbook of Statistical Analyses using R shows you how to easily use R to effectively evaluate your data. With numerous real-world examples, it emphasizes the practical application and interpretation of results.
 

Reviews of the second edition:

"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

"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),

"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
 



Reviews of 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


Contents

- An Introduction to R
- Data Analysis Using Graphical Displays
- Simple Inference
- Conditional Inference
- Analysis of Variance
- Simple and Multiple Linear Regression
- Logistic Regression and Generalized Linear Models
- Density Estimation
- Recursive Partitioning
- Scatterplot Smoothers and Generalized Additive Models
- Survival Analysis
- Analyzing Longitudinal Data I
- Analyzing Longitudinal Data II
- Simultaneous Inference and Multiple Comparisons
- Meta-Analysis
- Principal Component Analysis
- Multidimensional Scaling
- Cluster Analysis
- Bibliography
- Index


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Biography

Brian S. Everitt is Professor Emeritus at King's College, University of London. Torsten Hothorn is Professor of Biostatistics in the Institut fur Statistik at Ludwig-Maximilians-Universität München.

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