An introduction to the "new statistics" of resampling will be offered Sept.
20-22 in Washington, DC, and February 8-9 in Orlando, FL. Resampling -
bootstrap, permutation, and other tests - has revolutionized the field of
statistics. Resampling is now the method of choice for confidence limits,
hypothesis tests, and other everyday inferential problems.

Resampling is for both experts and non-statisticians. With resampling
procedures you use the given sample data to repeatedly simulate
hypothetical "re-samples", recalculating the statistic of interest. No
"black-box" formulas will hide the underlying statistical procedure.

For information contact:  Peter Bruce, syoung@netaxs.com
(Phone 703-522-2713)

Outline:

I.  A BRIEF HISTORY AND ROADMAP
- Early prigins of resampling
- Recent reemergence
- Theory of resampling

II.  HYPOTHESIS TESTING
- Measured data and counted data
- Single sample
- Two samples
- Multiple samples
- Bootstrap tests
- Permutation tests
- Tests of proportions
- Imbalanced sample sizes
- Correlation
- Regression

III.  CONFIDENCE INTERVALS
- Bootstrap confidence intervals
- Measured data and counted data
- Sample size determination

IV.  RESAMPLING'S RELATIONSHIP TO CONVENTIONAL PARAMETRIC METHODS

This is an introductory course, with no specific pre-requisites, though a
familiarity with basic probability and descriptive statistics will help.
 
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