SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition

Kleinman, Ken, Horton, Nicholas J.

ISBN 10: 1466584491 / ISBN 13: 9781466584495

Published by Chapman and Hall/CRC, 2014

About this Item

Like New.

Seller Inventory # ERICA79014665844916

Bibliographic Details

• Title: SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition
• Publisher: Chapman and Hall/CRC
• Publication Date: 2014
• Language: English
• ISBN 10: 1466584491
• ISBN 13: 9781466584495
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: Like New
• Book Type: book

About this title

Synopsis

An Up-to-Date, All-in-One Resource for Using SAS and R to Perform Frequent TasksThe 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 EditionThis 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 SystemsThrough 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.

About the Author

Ken Kleinman, Nicholas J. Horton