Five years ago I recommended the book Learning Base R. Here’s the last paragraph of my review:
Now there are more books on R, and some are more approachable to non-statisticians. The most accessible one I’ve seen so far is Learning Base R by Lawrence Leemis. It gets into statistical applications of R—that is ultimately why anyone is interested in R—but it doesn’t start there. The first 40% or so of the book is devoted to basic language features, things you’re supposed to pick up by osmosis from a book focused more on statistics than on R per se. This is the book I wish I could have handed my programmers who had to pick up R.
Now there’s a second edition. The author has gone through the book and made countless changes, many of them small updates that might be unnoticeable. Here are some of the changes that would be more noticeable.
- There are 265 new exercises.
- Chapter 26 (statistics) and Chapter 28 (packages) got a complete overhaul.
- Dozens of new functions are introduced (either in the body of the text or through exercises).
- New sections include the switch function (in Chapter 13 on relational operators), algorithm development (in Chapter 23 on iteration), analysis of variance (in Chapter 26 on statistics), and time series analysis (in Chapter 26 on statistics).
I was impressed with the first edition, and the new edition promises to be even better.
The book is available at Barnes & Noble and Amazon.