Synopsis
In SAS Statistics by Example, Ron Cody offers up a cookbook approach for doing statistics with SAS. Structured specifically around the most commonly used statistical tasks or techniques--for example, comparing two means, ANOVA, and regression--this book provides an easy-to-follow, how-to approach to statistical analysis not found in other books.
For each statistical task, Cody includes heavily annotated examples using ODS Statistical Graphics procedures such as SGPLOT, SGSCATTER, and SGPANEL that show how SAS can produce the required statistics. Also, you will learn how to test the assumptions for all relevant statistical tests. Major topics featured are correlation, inferential statistics, descriptive statistics, categorical data analysis, simple linear regression, comparing means, multiple regression, logistic regression, non-parametric tests, and power and sample size.
This is not a book that teaches statistics. Rather, SAS Statistics by Example is perfect for intermediate to advanced statistical programmers who know their statistics and want to use SAS to do their analyses.
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About the Author
Ron Cody, EdD, a retired professor from the Robert Wood Johnson Medical School now works as a private consultant and a national instructor for SAS Institute Inc. A SAS user since 1977, Ron's extensive knowledge and innovative style have made him a popular presenter at local, regional, and national SAS conferences. He has authored or co-authored numerous books, such as Learning SAS by Example: A Programmer's Guide; SAS Statistics by Example, Applied Statistics and the SAS Programming Language, Fifth Edition; The SAS Workbook; The SAS Workbook Solutions; Cody's Data Cleaning Techniques Using SAS, Second Edition; Longitudinal Data and SAS: A Programmer's Guide; SAS Functions by Example, Second Edition, and Cody's Collection of Popular Programming Tasks and How to Tackle Them, and Test Scoring and Analysis Using SAS, as well as countless articles in medical and scientific journals.
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