This extremely useful paper reminds us of common statistical mistakes made in articles and papers: ‘Ten common statistical mistakes to watch out for when writing or reviewing a manuscript‘.
Those are:
- absence of an adequate control condition or group
- interpreting comparisons between two effects without directly comparing them as a full group
- inflating the number of units of analysis
- spurious correlations (example single weird value)
- using too small samples
- circular analysis (retrospectively selecting features of the data to characterize the dependent variables, resulting in a distortion of the resulting statistical test)
- too much flexibility of analysis
- failure to correct for multiple comparisons in exploratory analysis)
- over-interpreting non-significant results
- confusing correlation and causation
Quite a useful checklist to use the next time you review a paper based on statistical analysis!
