A Handbook of Statistical Analyses Using R
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A Handbook of Statistical Analyses Using R

A Handbook of Statistical Analyses Using R


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About the Book

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.

Table of 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.

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 fur Statistik at Ludwig-Maximilians-Universit�Munchen.

Review :
! 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


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Product Details
  • ISBN-13: 9781420079340
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Language: English
  • No of Pages: 376
  • ISBN-10: 1420079344
  • Publisher Date: 20 Jul 2009
  • Binding: Digital (delivered electronically)
  • No of Pages: 376


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