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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Dirk Taeger, Institute for Prevention and Occupational Medicine of the German Social
Accident Insurance, Institute of the Ruhr-Universität Bochum (IPA), Bochum, Germany
Sonja Kuhnt, Department of Computer Science, Dortmund University of Applied Sciences
and Arts, Dortmund, Germany
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 fi nd this book a valuable
resource. Students using SAS and R will also fi nd it an excellent choice for reference
and data analysis.
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 fi nd this book a valuable
resource. Students using SAS and R will also fi nd it an excellent choice for reference
and data analysis.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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