SAS and R: Data Management, Statistical Analysis, and Graphics, 2nd Edition

An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent Tasks
The first edition of this popular guide provided a path between SAS and R using an easy-to-understand, dictionary-like approach. 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 book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, and graphics, along with more complex applications.

New to the Second Edition
This edition now covers RStudio, a powerful and easy-to-use interface for R. 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. It also includes extended examples of simulations and many new examples.

Enables Easy Mobility between the Two Systems
Through the extensive indexing and cross-referencing, users can directly find and implement the material they need. SAS users can look up tasks in the SAS index and then find the associated R code while R users can benefit from the R index in a similar manner. Numerous example analyses demonstrate the code in action and facilitate further exploration. The datasets and code are available for download on the book’s website.

Table of Contents

Chapter 1 – Data input and output
Chapter 2 – Data management
Chapter 3 – Statistical and mathematical functions
Chapter 4 – Programming and operating system interface
Chapter 5 – Common statistical procedures
Chapter 6 – Linear regression and ANOVA
Chapter 7 – Regression generalizations and modeling
Chapter 8 – A graphical compendium
Chapter 9 – Graphical options and configuration
Chapter 10 – Simulation
Chapter 11 – Special topics
Chapter 12 – Case studies

Appendix A – Introduction to SAS
Appendix B – Introduction to R and RStudio
Appendix C – The HELP study dataset