Data Analysis and Graphics Using R - An Example-Based Approach

John Maindonald and John Braun     2nd edn, Cambridge University Press, January 2007    

Documents and code that supplement the book are available thus:

Corrections (18 Jan 2009)
1st printing   (Booklet format; click here) pp. 16, 39, 40, 42, 55, 70, 72, 105, 106, 111, 115, 189, 196, 207, 209, 211, 222, 266, 308, 309, 311, 310, , 314, 325, 343, 348, 426, 433, 462, 464
2nd printing   (Booklet format; click here) pp.105, 115, 211, 310, , 314, 343, 348, 462, 464
GUIs, easier ways in lattice, ARIMA modeling using the forecast package, and changes to mcmcsamp() output objects.
Reproduce book's graphs
There is a choice of source (.R) and image (.RData) files.
R code, chapter by chapter
Has R code script files for each of the 14 chapters.
Solutions to exercises
Ch 1:8/21 (8 of 21); 2:7/13; 3:7/11; 4:13/23; etc (Click for details)
Laboratory exercises
Summary details of 16 sets of laboratory (2+ hour. some shorter) exercises [plus notes on use of R's Sweave() function to generate the LaTeX files for the exercises]. These exercises substantially supplement exercises in the book.
Updates to the text, and notes additional to the text
Updates I: 7Dec2007: Supplementary notes re xyplot() (pp.55-56, etc), AOV table on p.121, measurement error models (pp.207, 209), predict() for GLMs (Ch 8), etc;   Updates II: 23Dec2008: GUIs, easier ways in lattice, ARIMA modeling using the forecast package, and changes to mcmcsamp() output objects.
Notes additional to the text: Overheads for a talk on multilevel models; Chapter 10 using lme(); Lattice and other graphics; Least squares computation; Theory of Generalized Linear Models; Regression in Practice; Comparative a/c of lda(), qda() and logistic regression; Analysis of microarray data; R talks to LaTeX (Sweave). These notes treat topics that get brief mention in the text.
Draft Changes and Additions
Draft of Selected Changes and Additions in a Projected 3rd Edition of Data Analysis and Graphics Using R (late 2009, perhaps) Discusses R GUIs, lattice and interaction with lattice plots, ggplot2, measurement error models, and automated choice of ARIMA models using the forecast package from the forecasting package bundle.
R Course Overheads
Overheads for a course that is based on the text.
R setup and environment
Brief comments and links for installation of R; Use of R with the Tinn-R Windows editor; Brief notes on other editor interfaces.
First edition
Additional materials, relevant to the 1st edition.

See Also

DAAG package     older versions