<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
Using SAS for Data Management, Statistical Analysis, and Graphics
โ Scribed by Ken Kleinman, Nicholas J. Horton
- Year
- 2010
- Tongue
- English
- Leaves
- 308
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
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<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
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
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 through the extensive, idiosyncratic, and sometimes unwieldly software documentation and vast number of add-on packages. Organized by short
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