**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.

- Cover
- Title Page
- Copyright
- Dedication
- Preface
- Part I: Introduction
- Part II: Normal Distribution
- Part III: Binomial Distribution
- Part IV: Other Distributions
- Part V: Correlation
- Part VI: Nonparametric Tests
- Part VII: Goodness-of-Fit Tests
- Part VIII: Tests on Randomness
- Part IX: Tests on Contingency Tables
- Part X: Tests on Outliers
- Part XI: Tests in Regression Analysis
- Appendix A: Datasets
- Appendix B: Tables
- Glossary
- Index