A Handbook of Statistical Analyses Using R, Second Edition - Softcover

Críticas

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

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

Reseña del editor

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.