Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
24.03.2014
Verlag
John Wiley & Sons IncSeitenzahl
312
Maße (L/B/H)
24,4/17,5/2,3 cm
Gewicht
635 g
Auflage
1. Auflage
Sprache
Englisch
ISBN
978-1-119-95021-9
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.
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.
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.
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.
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