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

John Maindonald and John Braun     3rd edn, Cambridge University Press, (May 2010 in UKJune 2010 in USA)   

Documents and code that supplement the book are available thus:
Updates, 2010 printingp.31 (code for Fig.1.3); p.101 (Ex 13, wrong stationary values); p.187, ss 6.3.2 (definition of Cp); pp.210-211, ss 6.8.4 (multiplier omitted); p.238, ss 7.6.1 (lm should be gam); p.295, Sec 9.2, fn 5 (numerical error); p.298, Sec 9.2 (updated computer output); p.350, Ex 5 (hint); pp.483-484, ss 15.5.3 (alternative using layering); p.491, Table 15.2 (additional note)
Updates, 2010 & 2011 printings Issues include corrections to code on pp31, 88, 332 and 407, corrected Sun/Cloud/Rain proportions in Exercise 13 on p.101, and 0.00070 corrected to 0.0070 on p.177, line 2. Additionally, the updates to the 2013 printing apply here also.
Updates, 2010, 2011 & 2013 printings These include code changes made necessary by changes in R functions, corrections, and some improvements in code style. Some new functionalities are noted.
Lattice graphics Layering in lattice (describes abilities, noted briefly in the second printing, that build up graphs in layers); Control of bounding boxes in lattice graphs.
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 15 chapters.
Solutions to exercises Ch 1:8/21 (8 of 21); 2:7/14; 3:6/13; 4:13/22; 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.
Notes additional to the text Overheads for a talk on multilevel models; Chapter 10 using lme(); Least squares computation; Theory of Generalized Linear Models; Regression in Practice; Smoothing terms in GAM models; Comparative a/c of lda(), qda() and logistic regression; Ordination; Spatial methods in R; Analysis of microarray data. These notes extend or offer a different perspective on, the discussion in the text.
R talks to LaTeX (Sweave)
or to Markdown or HTML
Use knitr to process a document that includes R code within a LaTeX file that has Sweave type markup, or within a Markdown file that has R Markdown markup, or within an HTML files that has R HTML markup. The markup settings control what combination of R code and output (including tables and graphs) is included in the final document.
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 RStudio; Brief notes on other editor interfaces.
First edition Additional materials, relevant to the 1st edition.
Second edition Additional materials, relevant to the 2nd edition

See Also

DAAG package     older versions