| Updates, 2010 printing | p.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 |
DAAG package
older versions