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Sas And R Data Management Statistical Analysis And Graphics Second Edition 2nd Edition Ken Kleinman

  • SKU: BELL-4739676
Sas And R Data Management Statistical Analysis And Graphics Second Edition 2nd Edition Ken Kleinman
$ 31.00 $ 45.00 (-31%)

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Sas And R Data Management Statistical Analysis And Graphics Second Edition 2nd Edition Ken Kleinman instant download after payment.

Publisher: Chapman and Hall/CRC
File Extension: PDF
File size: 6.1 MB
Pages: 468
Author: Ken Kleinman, Nicholas J. Horton
ISBN: 9781466584495, 1466584491
Language: English
Year: 2014
Edition: 2

Product desciption

Sas And R Data Management Statistical Analysis And Graphics Second Edition 2nd Edition Ken Kleinman by Ken Kleinman, Nicholas J. Horton 9781466584495, 1466584491 instant download after payment.

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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