9781466584495-1466584491-SAS and R

SAS and R

ISBN-13: 9781466584495
ISBN-10: 1466584491
Edition: 2
Author: Ken Kleinman, Nicholas J. Horton
Publication date: 2014
Publisher: Routledge
Format: Hardcover 470 pages
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Book details

ISBN-13: 9781466584495
ISBN-10: 1466584491
Edition: 2
Author: Ken Kleinman, Nicholas J. Horton
Publication date: 2014
Publisher: Routledge
Format: Hardcover 470 pages

Summary

SAS and R (ISBN-13: 9781466584495 and ISBN-10: 1466584491), written by authors Ken Kleinman, Nicholas J. Horton, was published by Routledge in 2014. With an overall rating of 3.9 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent SAS and R (Hardcover) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $6.57.

Description

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.

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