**Second edition now available**: click HERE for more information.

This book shows how equivalent statistical methods can be applied in either SAS or R, enabling users of each software package to learn how to apply the methods in the other. It covers data management, simple statistical procedures, modeling and regression, and graphics. Each section begins with a brief introduction to the procedures and then presents the code for each software side-by-side. The book provides detailed worked examples together with output from the software to illustrate how the methods are applied in practice. It also includes an index for both SAS and R, which will be useful to a wide range of users.

"As the authors point out in the Introduction, the book functions like an English-French dictionary. The material is organized by task. By looking up a particular task you wish to perform, R and SAS code are presented and briefly explained. ... If you use both SAS and R on a regular basis, get this book. If you know one of the packages and are learning the other, you may need more than this book, but get this book too." - Charles Heckler, *Technometrics* (2010).

"For statisticians with knowledge of both SAS and R programming this book provides a useful resource to understand the differences between SAS and R codes and can be used for browsing and for finding particular SAS and R functions to perform common tasks. The book will strengthen the analytical abilities of relatively new users of either system by providing them with a concise reference manual and annotated examples executed in both packages. Professional analysts as well as statisticians, epidemiologists and others who are engaged in research or data analysis will find this book very useful. The book is comprehensive and covers an extensive list of statistical techniques from data management to graphics procedures, cross-referencing, indexing and good worked examples in SAS and R at the end of each chapter."
- *Significance* (2010)

"... this book does exactly what it promises: it facilitates a translation between SAS and R, without getting overly detailed or technical. It is mainly useful as a starting point for those who already know either R or SAS, and want to learn the other language, without going over extensive manuals or introductory texts. " - Jeroen Ooms, *Journal of Statistical Software* (2011).