That is what this book is designed to do and it is absolutely excellent for this purpose.

As such, I have been looking, for years, for a dictionary to translate between R and SAS. 'I am a long time SAS user who is surrounded by R experts. 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). If you use both SAS and R on a regular basis, get this book. By looking up a particular task you wish to perform, R and SAS code are presented and briefly explained. 'As the authors point out in the Introduction, the book functions like an English-French dictionary. It also includes extended examples of simulations and many new examples. It incorporates a number of additional topics, including using application program interfaces (APIs), accessing data through database management systems, using reproducible analysis tools, and statistical analysis with Markov chain Monte Carlo (MCMC) methods and finite mixture models. This edition now covers RStudio, a powerful and easy-to-use interface for R. The book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications. Retaining the same accessible format, SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition explains how to easily perform an analytical task in both SAS and R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach.

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

Sas tools for data analysis