While there are many tools you can use to work with data science and statistics, there's an increasing focus on the R programming language, and the books in this section teach different aspects of R and its use for data science.  

R For Everyone, 2nd Ed

Author: Jared P. Lander
Publisher: Addison Wesley
Pages: 560
ISBN: 978-0134546926

Giving this book 4.5 stars, Mike James points out that R really isn't for everyone. This book steers a balanced course between describing the stats you can do using R and concentrating on the programming language.

Mike concluded that while this isn't the best possible book on R, it is good enough for you to think about adding to your collection. It is a good book for the R beginner, but be warned there are some advanced topics when it comes to the stats. Overall the stats isn't explained as theory, but as practice, meaning that if you hope to use any of them, and reason about them, you will need to read another book. Recommended to R beginners who know enough stats not to worry about the advanced material.

R for Data Analysis (In Easy Steps) 2nd Ed

Author: Mike McGrath
Publisher: Easy Steps
Pages: 192
ISBN: 978-1840789980

This book takes a very simple approach to using the R language and using it to do simple things - that often turn out to be harder than you might expect. This book explains in detail how to do those simple things, and impressed Mike James enough for him to award it the maximum five stars. It is worth pointing out that it is in full color and remarkable value for money.

This is a fairly basic introduction to R and it doesn't reach many of the features and facilities of the language. The book also isn't about statistics or modelling. However, within those limits, this is a very good book and Mike recommends you ignore any reviews that say otherwise simply because they have the level and intent of the book wrong.

R in 24 Hours

Author: Andy Nicholls, Richard Pugh, Aimee Gott
Publisher: Sams 
Pages:624 
ISBN: 978-0672338489

This book is mostly about how to program in R and how to work with data. As with other titles in the series, it is divided into 24 sections, each of which is supposed to take an hour.

 Mike James concluded that overall this is a good book, and gave it four stars, saying the most important thing to know is that it won't teach you statistics and it is about programming in R, the only real problem being that the presentation isn't from a programming point of view. If you are a programmer and want to learn R then you will find it hard going because it hardly makes use of the deeper ideas of programing to make things seem easier and logical.

If you aren't a programmer then you are likely to find the approach good as long as you take your time and come back to the book when you need to clarify some aspect of using R. 

Recommended as long as you know stats and don't want to become a programmer in general - just an R programmer.

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