Mathematical Statistics

A summary by Bernhard Kabelka,
based on the lecture by Prof. Grill in 2002/03
 
Version 1.02 (March 15, 2004)

The author would like to stress that

1. this summary was created without the knowledge or cooperation of Prof. Grill,
2. although every effort has been made in order to supply an accurate and complete summary, mistakes cannot be ruled out (if you spot a mistake, please inform the author, preferably by sending an email to stat_v1-02.stochast.bkabelka@spamgourmet.com),
3. reading this summary does not make up for attending the lectures or reading the script.

1. Introduction
    
2. Basic Theory of Estimation
   • Point Estimation
   • Confidence Intervals
      
3. Testing
   • The Neyman-Pearson and the Likelihood Ratio Test
   • Unbiased Tests
   • Special tests for the normal distribution
     • Tests for
     • Tests for
     • Two-sample tests
        
4. Analysis of Variance
   • The Fisher-Cochran Theorem
   • One-Way Analysis of Variance
   • Two-Way Analysis of Variance
      
5. Linear Regression
   • Simple Linear Regression
   • Multiple Linear Regression
   • Other Functional Relations
      
6. The -Family of Tests
   • The -Goodness-of-Fit Test
   • The -Test of Independence
   • The -Test of Homogeneity
      
7. The Kolmogorov-Smirnov Test
   • One-Sample Test
   • Two-Sample Test
      
8. Appendix
   1. Probability Distributions
   2. German Translations of Technical Terms

This summary may also be downloaded as PDF- and as PostScript-File.

© Bernhard Kabelka 2003 – 2004
Last modified: March 20, 2004
 
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