Common Mistakes in Using Statistics - Spotting Them and Avoiding Them

2010 Summer Statistics Institute Course, University of Texas at Austin

May 24 - 27, 2010 

Course Notes 

External Links

Rice Virtual Lab in Statistics Sampling Distribution Simulation

Bioconsulting Confidence Interval Simulation

R. Webster's Confidence Interval Simulation

W. H Freeman's Confidence Interval Simulation

The Rice Virtual Lab in Statistics Confidence Interval Simulation

Rice Virtual Lab in Statistics Robustness Simulation

Claremont University's Wise Project's Statistical Power Applet

Jerry Dallal's Simulation of Multiple Testing
This simulates the results of 100 independent hypothesis tests, each at 0.05 significance level. Click the "test/clear" button  to see the results of one set of 100 tests (that is, for one sample of data). Click the button two more times (first to clear and then to do another simulation) to see the results of another set of 100 tests (i.e., for another sample of data). Notice as you continue to do this that i) which tests give type I errors (i.e., are statistically significant at the 0.05 level) varies from sample to sample, and ii) which samples give type I errors for a given test varies from test to test. (To see the latter point, it may help to focus just on the first column.)

Negative Consequences of Dichotomizing Continuous Predictor Variables

Website on Common Misteaks Mistakes in Using Statistics

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