Category Archives: non-normality

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

Posted in assumptions, Biostatistics, heteroscedasticity, non-normality, non-parametric statistics, Statistics, Uncategorized | 14 Comments

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

Posted in ANOVA, assumptions, Biostatistics, non-normality, non-parametric statistics, Ordinal, Statistics | 2 Comments

10. Parametric or non-parametric 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

Posted in assumptions, Biostatistics, Dichotomization, Effect Size, heteroscedasticity, Interval, non-normality, non-parametric statistics, Ordinal, p-values, Power, Statistical, Statistics | 2 Comments

18. Percentage Change from Baseline – Great or Poor?

Everything should be made as simple as possible, but no simpler. – Attributed to Albert Einstein *** In my third and forth blog I addressed useful ways to present the results of an analysis.  Of course, p-values wasn’t it.  I … Continue reading

Posted in Analysis of Covariance, assumptions, Effect Size, heteroscedasticity, non-normality, percentage change from baseline | 18 Comments

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, non-normality, non-parametric statistics, p-values, Power, t-test | 2 Comments