This book provides a reference guide to statistical tests and their application to data using SAS and R. A general summary of statistical test theory is presented, along with a general description for each test, together with necessary prerequisites, assumptions, and the formal test problem. Num Pages: 306 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 252 x 168 x 20. Weight in Grams: 626. . 2014. . . . . Books ship from the US and Ireland.

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Bibliographic Details

Title: Statistical Hypothesis Testing with SAS and R
Publisher: John Wiley & Sons Inc
Publication Date: 2014
Language: English
ISBN 10: 111995021X
ISBN 13: 9781119950219
Binding: Hardcover
Condition: New

About this title

Synopsis

A comprehensive guide to statistical hypothesis testing with examples in SAS and R

When analyzing datasets the following questions often arise:

Is there a short hand procedure for a statistical test available in SAS or R?
If so, how do I use it?
If not, how do I program the test myself?

This book answers these questions and provides an overview of the most common
statistical test problems in a comprehensive way, making it easy to find and perform
an appropriate statistical test.

A general summary of statistical test theory is presented, along with a basic
description for each test, including the necessary prerequisites, assumptions, the
formal test problem and the test statistic. Examples in both SAS and R are provided,
along with program code to perform the test, resulting output and remarks
explaining the necessary program parameters.

Key features:
• Provides examples in both SAS and R for each test presented.
• Looks at the most common statistical tests, displayed in a clear and easy to follow way.
• Supported by a supplementary website http://www.d-taeger.de featuring example
program code.

Academics, practitioners and SAS and R programmers will find this book a valuable
resource. Students using SAS and R will also find it an excellent choice for reference
and data analysis.

About the Author

Dirk Taeger, Institute for Prevention and Occupational Medicine of the German Social
Accident Insurance, Institute of the Ruhr-Universit�t Bochum (IPA), Bochum, Germany

Sonja Kuhnt, Department of Computer Science, Dortmund University of Applied Sciences
and Arts, Dortmund, Germany

"About this title" may belong to another edition of this title.

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