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 BioStatistical Blog
 1. Statistic’s Dirty Little Secret
 1.A Another view on testing by Peter Flom, PhD
 1.B Am I a nattering nabob of negativism?
 2. Why do we compute pvalues?
 3. Meaningful ways to determine the adequacy of a treatment effect when you have an intuitive knowledge of the dependent variable
 4. Meaningful ways to determine the adequacy of a treatment effect when you lack an intuitive knowledge of the dependent variable
 5. Accepting the null hypothesis
 6. ‘Lies, Damned Lies, and Statistics’ part 1, and Analysis Plans, an essential tool
 7. Assumptions of Statistical Tests
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 Allen Fleishman on 24. Simple, but SimpleMinded
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 Allen Fleishman on 24. Simple, but SimpleMinded
 Victor Levenson on 24. Simple, but SimpleMinded
 Allen Fleishman on 12. Significant pvalues in small samples
 Merm on 12. Significant pvalues in small samples
 Allen Fleishman on 12. Significant pvalues in small samples
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 Allen Fleishman on 12. Significant pvalues in small samples
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Category Archives: nonparametric statistics
7. Assumptions of Statistical Tests
“All models are incorrect. Some are useful.” George Box *** When you do a statistical test, you are, in essence, testing if the assumptions are valid. We are typically only interested in one, the null hypothesis. That is, the assumption … Continue reading
7a. Assumptions of Statistical Tests: Ordinal Data
In my ‘7. Assumptions of Statistical Tests‘, there was a glaring omission (at least glaring for me): no discussion of ordinal data. I felt that I let my readers down, by glossing over this issue. Time to repair my quite … Continue reading
8. What is a Power Analysis?
People who haven’t the time to do things ‘perfectly’, always have time to do them over. Measure once, cut twice. Measure twice, cut once. ‘My god, you’ve conclusively proven it. Time equals Money.’ *** Cost for Failure Every CEO I’ve … Continue reading
10. Parametric or nonparametric analysis – Why one is almost useless
… ‘If you lost your watch in that dark alley, why are we looking here?’ ‘Well, <hic> there’s light here.’ (old chestnut) *** In my last blog, I stated that we should avoid dichotomizing as it throws away a lot … Continue reading
19. A Reconsideration of My Biases
No virtual observations were harmed in the running of this study. A man with one watch knows what time it is. A man with two is not sure, at least for the Wilcoxon test. And don’t try this at home, … Continue reading
Posted in ANOVA, Effect Size, nonnormality, nonparametric statistics, pvalues, Power, ttest
2 Comments
23. Small N study to publish or not?
The following question was sent to me, I thought it useful enough for a full elaboration: Submitted on 2014/05/12 at 8:23 am Dr. Fleishman, I am so happy I found your site. I have been trying to decide how to best … Continue reading