This list will help non-scientists to interrogate advisers and to grasp the limitations of the evidence, say, William J. Sutherland, David Spiegelhalter and Mark A. Burgman.
- Differences and chance cause variation.
- No measurement is exact.
- Bias is rife
- Bigger is usually better for sample size.
- Correlation does not imply causation.
- Regression to the mean can mislead.
- Extrapolating beyond the data is risky.
- Beware the base-rate fallacy.
- Controls are important.
- Randomization avoids bias.
- Seek replication, not pseudoreplication.
- Scientists are human.
- Significance is significant.
- Separate no effect from non-significance.
- Effect size matters.
- Study relevance limits generalizations.
- Feelings influence risk perception.
- Dependencies change the risks.
- Data can be dredged or cherry picked.
- Extreme measurements may mislead.
References: https://www.nature.com/news/policy-twenty-tips-for-interpreting-scientific-claims | Twenty tips for interpreting scientific claims [PDF]
