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)   

New text that builds on third edition

The manuscript is substantially complete, and should appear in print in late 2022.
New or substantially revised content from the 2018 draft  

Link to planned GitHub Pages resources for new text.
(As of January 2021, this is at a very early stage of development)

Documents and code that supplement the book (primarily, the 3rd edition) 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). NB also the updates to the 2011 and 2013 printings, which apply here also.
Updates, 2011 printing 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. NB also the updates to the 2013 printing, which apply here also.
Updates, 2013 printing   These include code changes made necessary by changes in R functions, corrections, and some improvements in code style. Some new functionalities are noted, which will likely get attention in the planned new text.
Updates, 2013 printing, in booklet format
Chapter 10 update
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.
Code for graphs, by chapter There is a choice of source (.R) and image (.RData) files. RStudio Code Notebooks are also provided. (Updated Sept 2014.)
R code, by chapter Has R code script files for each of the 15 chapters. RStudio Code Notebooks are also provided. (Updated Sept 2014.)
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.
Further related content See especially the GitHub repositories 'learnR' ("Learning R") and 'dataThoughts'.
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