Statistical Hypothesis Testing with SAS and R

Book description

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.

    Table of contents

    1. Cover
    2. Title Page
    3. Copyright
    4. Dedication
    5. Preface
    6. Part I: Introduction
      1. Chapter 1: Statistical hypothesis testing
        1. 1.1 Theory of statistical hypothesis testing
        2. 1.2 Testing statistical hypothesis with SAS and R
        3. 1.3 Presentation of the statistical tests
        4. References
    7. Part II: Normal Distribution
      1. Chapter 2: Tests on the Mean
        1. 2.1 One-sample tests
        2. 2.2 Two-sample tests
        3. References
      2. Chapter 3: Tests on the variance
        1. 3.1 One-sample tests
        2. 3.2 Two-sample tests
        3. References
    8. Part III: Binomial Distribution
      1. Chapter 4: Tests on proportions
        1. 4.1 One-sample tests
        2. 4.3 K-sample tests
        3. References
    9. Part IV: Other Distributions
      1. Chapter 5: Poisson distribution
        1. 5.1 Tests on the Poisson parameter
        2. References
      2. Chapter 6: Exponential Distribution
        1. 6.1 Test on the parameter of an exponential distribution
        2. Reference
    10. Part V: Correlation
      1. Chapter 7: Tests on association
        1. 7.1 One-sample tests
        2. 7.2 Two-sample tests
        3. References
    11. Part VI: Nonparametric Tests
      1. Chapter 8: Tests on location
        1. 8.1 One-sample tests
        2. 8.2 Two-sample tests
        3. 8.3 K-sample tests
        4. References
      2. Chapter 9: Tests on scale difference
        1. 9.1 Two-sample tests
        2. References
      3. Chapter 10: Other Tests
        1. 10.1 Two-sample tests
        2. References
    12. Part VII: Goodness-of-Fit Tests
      1. Chapter 11: Tests on normality
        1. 11.1 Tests based on the EDF
        2. 11.2 Tests not based on the EDF
        3. References
      2. Chapter 12: Tests on other Distributions
        1. 12.1 Tests based on the EDF
        2. 12.2 Tests not based on the EDF
        3. References
    13. Part VIII: Tests on Randomness
      1. Chapter 13: Tests on randomness
        1. 13.1 Run tests
        2. 13.2 Successive difference tests
        3. References
    14. Part IX: Tests on Contingency Tables
      1. Chapter 14: Tests on contingency tables
        1. 14.1 Tests on independence and homogeneity
        2. 14.2 Tests on agreement and symmetry
        3. 14.3 Test on risk measures
        4. References
    15. Part X: Tests on Outliers
      1. Chapter 15: Tests on outliers
        1. 15.1 Outliers tests for Gaussian null distribution
        2. 15.2 Outlier tests for other null distributions
        3. References
    16. Part XI: Tests in Regression Analysis
      1. Chapter 16: Tests in Regression Analysis
        1. 16.1 Simple linear regression
        2. 16.2 Multiple linear regression
        3. References
      2. Chapter 17: Tests in variance analysis
        1. 17.1 Analysis of variance
        2. 17.2 Tests for homogeneity of variances
        3. References
    17. Appendix A: Datasets
    18. Appendix B: Tables
    19. Glossary
    20. Index

    Product information

    • Title: Statistical Hypothesis Testing with SAS and R
    • Author(s):
    • Release date: March 2014
    • Publisher(s): Wiley
    • ISBN: 9781119950219