Handbook of Statistical Analyses Using R

I just finished the second edition of A Handbook of Statistical Analyses Using R (Authors: Everitt and Hothorn; ISBN: 9781420079333).

Overall, a great reference and handbook. While I never looked at the first edition, I was happy to see that the publishers updated the R packages from the first edition and placed them on CRAN. The old package is HSAUR and the new package for the second edition is HSAUR2. My version of R (2.8.1) would not install the HSAUR2 package directly from CRAN, but it was a simple matter to download the package zip file then install it from my desktop file system.

The book is mostly geared toward someone that is new to R, but it still provided a broad enough coverage of useful topics that it will be a great reference to have handy. The vast size of R features, functions, and extensions can be a bit daunting even after using R for sometime. I have used R for years, but I don't use it everyday. So I plan to use the handbook as a well-organized reference for features that are commonly needed. Maybe I haven't used something basic for a long time, and the reference will be useful as a quick primer on a variety of topics.

The coverage of material in the book is really good and it goes beyond the basics: some basic stats, ANOVA, regression, logistic regression, generalized linear models, density estimation, partitioning, longitudinal analysis, inference, meta-analysis, component analysis, scaling, clustering, and more.

Advanced math and statistics are truly fundamental to AI and cognitive modeling. You need to keep a good set of tools handy if you want excellence in your work. I like R and I like the handbook as a reference.