The author has made a very serious effort to introduce entry-level students of statistics to the open-source software package R. One mistake most authors of similar texts make is to assume some basic level of familiarity, either with the subject to be taught, or the tool (the software package) to be used in teaching the subject.

This book does not fall into either trap. About one-fifth of the book is a collection of Appendices that explains how to install the software package in your computer for three different operating systems, how to use interfaces, graphics, and how to program. This is great, since this will broaden the reach of the book by attracting self-instructing readers who otherwise would not know how to start.

As far as the text itself goes, the examples and exercises are well-chosen; they concern questions to which we would actually like to know the answer. Topical coverage is comparable to more traditional introductory textbooks, though the treatment is somewhat less formal than the average.

My only critical remark is that none of the exercises and problems have their solution included in the book. I do understand that there is a website with selected solutions, and that instructors can receive a full solution manual. I also understand that the book involves the use of R, and therefore, the student using the book will spend a lot of time at a computer, so that it's not unreasonable to assume that he or she might as well check the solutions on the web. Still, we do not want to send the message that without immediate access to a software package, our fresh knowledge is useless, and indeed, there are a few exercises in the book that can be solved just by thinking. A few of these should have their solutions in the book, to encourage that kind of learning as well.

Miklós Bóna is Professor of Mathematics at the University of Florida.