This book goes well beyond how to use this statistical programming language to work with statistics and treats it as a proper programming language. It provides you with everything you need to know to use the R language.
Perhaps the most surprising thing I noticed in this book when I looked through the contents page before i started reading through the book itself was just how short the appendix is that explains how to install R onto your computer. The reason why that appendix is so short became obvious when I actually followed those instructions. R has to be just about the simplest programming language to install that I have come across.
Getting into the actual material in the book itself and in the introduction the object oriented approach of R is compared to the approach taken by other statistical languages. After having worked through some of the examples the author presents in the book I definitely agree with the comments on how much easier R is to use compared to SAS. I can't comment on the similar comparison with SPSS having never used that language. The functional approach with regard to avoiding loops in your processing is somewhat more familiar with respect to statistical programming.
The book presents all of its material in a very logical progression starting with the basics, moving through all of the regular statistics related topics and then moving on to more advanced programming topics beyond what would normally be covered in a book about a statistical language. Anyone with at least some knowledge of statistics or statistical programming languages should have no trouble in following through the various examples in the book in order to actually learn how to use R (at the time of writing this review I have read through the entire book but have only actually tried running some of the examples but I can't see any reason why the examples I haven't run yet would be any more difficult to work through than the ones I actually tried). The only people who might have trouble with learning R from this book are those without any knowledge of statistical programming who may not immediately understand the types of data structures that such a language uses which are somewhat different in some ways from what you'd expect in a programming language not specifically intended for statistical use. The book does define each structure sufficiently that those people should at least be able to figure out how the structures work even if it is not so obvious to them as to why the language supports those structures rather than what they are used to. It has been a while since I last did any statistical programming (using SAS) and so it took me a short while to re-familiarise myself with how statistical languages work.
With the R language being a free download available for all common operating system and with this book giving complete coverage of the language demonstrating that it is at least as powerful as other statistical languages, there is no reason why anyone with a need for statistical programming ought to choose any approach other than to obtain a copy of this book and work through it as far as they need to to obtain the required results. Any other approach would be more expensive and far less efficient.
This article written by Stephen Chapman, Felgall Pty Ltd.