Essential Statistics Using SAS University Edition

Nonfiction, Computers, Application Software, Business Software
Cover of the book Essential Statistics Using SAS University Edition by Geoff Der, Brian S. Everitt, SAS Institute
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Author: Geoff Der, Brian S. Everitt ISBN: 9781629600949
Publisher: SAS Institute Publication: December 9, 2015
Imprint: SAS Institute Language: English
Author: Geoff Der, Brian S. Everitt
ISBN: 9781629600949
Publisher: SAS Institute
Publication: December 9, 2015
Imprint: SAS Institute
Language: English

Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

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Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

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