I have been using R in statistics courses for a few years and there are many introductions to R that cover the command structure and the statistical techniques, but none of them look at R as a programming language and take you through the steps of learning to program with R.
This book takes you from the first simple steps through to simulation, matrices and iterative optimisation. It also includes a guide for good programming practice. It includes an explanation of Monte Carlo integration that anyone can understand and shows the benefits of learning through practice. This book makes probability so much more accessible to students by letting them see what is actually happening in a graphical and practical way.
I think the book is fantastic and well worth the money.
Very nice book, although it does require some advanced prior experience with programming and knowledge of math concepts, etc. So I don't think this is a book for people starting to learn R. However, after having some experience with R you can improve your skills with this book.
Having done a reasonable job of introducing the basic syntax of the R programming language, the book then lurches into some rather advanced and specialist subjects, for example dedicating a whole section to algorithms for generating random numbers (for an introductory text, you would probably just want to know about the rnorm function). If you are interested in Monte Carlo simulation or numerical optimisation using the R language, this is the book for you. Readers hoping to learn to use R to perform standard statistical testing will be disappointed.