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SAS statistics by example

Author: Ronald P Cody; SAS Institute.
Publisher: Cary, North Carolina : SAS Publishing, 2011. ©2011
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Cody, Ronald P.
SAS statistics by example.
Cary, N.C. : SAS Institute, 2011
(OCoLC)749870558
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Ronald P Cody; SAS Institute.
ISBN: 9781612900124 1612900127
OCLC Number: 771283139
Description: 1 online resource (xvi, 257 pages) : illustrations (some color)
Contents: An introduction to SAS --
Descriptive statistics : continuous variables --
Descriptive statistics : categorical variables --
Descriptive statistics : bivariate associations --
Inferential statistics : one-sample tests --
Inferential statistics : two-sample tests --
Inferential statistics : comparing more than two means --
Correlation and regression --
Multiple regression --
Categorical data --
Binary logistic regression --
Nonparametric tests --
Power and sample size --
Selecting random samples.
Responsibility: Ron Cody.

Abstract:

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 include descriptive statistics, one- and two-sample tests, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, 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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