Common Mistakes in Using Statistics - Spotting Them and Avoiding Them

2012 Summer Statistics Institute Course, University of Texas at Austin

May 21 - 24, 2012 

Course Notes 

Please Note:

    Day                                             Slides (2 per sheet)                                Appendix

1 (M May 21)                                     Slides Day 1                                    Appendix Day 1

2 (Tu May 22)                                    SlidesDay2Part1(1-24)            (No appendix for Day 2)
    (Be sure to download                      SlidesDay2Part2(25)
       all three files for Day 2)                SlidesDay2Part3(26 - 49)

3 (Wed May 23)                                  Slides Day 3                                    Appendix Day 3    Corrected version posted
                                                                                                                        3:25 pm, Saturday, May 19

4 (Th May 24)                                     Slides Day 4                                    Appendix Day 4                                      

External Links

Empirical Probability Example

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

p-value video

Website on Common Misteaks Mistakes in Using Statistics

    Content similar to the content of the course notes, but includes embedded links and more information.

Blog: Musings on Using and Misusing Statistics

A companion to the preceding website Common Mistakes in Using Statistics. It contains updates to that site and occasional comments on other things related to statistics that come to my attention. It may  be of interest to the following categories of people:

    Teachers of statistics (especially those, such as myself, who come from backgrounds other than statistics)
    Undergraduates and early graduate students in statistics
    Users of statistics (especially people who read research using statistics)

Last updated May 15, 2012