I'm a R programmer who has some familiarity with SAS. I knew early-on that SAS is a mountain to climb, I was looking for something that would assist me in handing tasks between the 2-systems. This book is the one. Excellent examples and numerous explanations makes this a no-brainer for people using
SAS and R: Data Management, Statistical Analysis, and Graphics, Second Edition
β Scribed by Ken Kleinman, Nicholas J. Horton
- Publisher
- Chapman and Hall/CRC
- Year
- 2014
- Tongue
- English
- Leaves
- 425
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 bookβs website.
β¦ Subjects
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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, a
<P><EM><U>Quick and Easy Access to Key Elements of Documentation</U> <BR>Includes worked examples across a wide variety of applications, tasks, and graphics</EM></P> <P>A unique companion for statistical coders, <STRONG>Using SAS for Data Management, Statistical Analysis, and Graphics</STRONG> pres
<P><EM><U>Quick and Easy Access to Key Elements of Documentation</U> <BR>Includes worked examples across a wide variety of applications, tasks, and graphics</EM></P> <P>A unique companion for statistical coders, <STRONG>Using SAS for Data Management, Statistical Analysis, and Graphics</STRONG> prese
Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate