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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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Stat comments and Questions
 Allen Fleishman on 22. A question on QoL, Percentage Change from Baseline, and CompassionateUsage Protocols
 Kate on 22. A question on QoL, Percentage Change from Baseline, and CompassionateUsage Protocols
 Allen Fleishman on 24. Simple, but SimpleMinded
 Victor Levenson on 24. Simple, but SimpleMinded
 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
 Phil Assheton on 12. Significant pvalues in small samples
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Category Archives: Variance
15. Variance, and ttests, and ANOVA, oh my!
Statistics – a specialty of mathematics whose basic tenant is ‘Exceptions prove the rule’. Mr. McGuire: I just want to say one word to you. Just one word. Benjamin: Yes, sir. Mr. McGuire: Are you listening? Benjamin: Yes, I am. … Continue reading
Posted in ANOVA, pvalues, ttest, Uncategorized, Variance
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16. Comparing many means – Analysis of VARIANCE?
What do you call a numbers cruncher who is creative? An accountant. What do you call a numbers cruncher who is uncreative? A statistician. *** In the last blog, I explored the meaning of variance. I said that variance is … Continue reading
Posted in ANOVA, Treatment Effect, Variance
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