Scientific literacy for politicians
In short, the concepts are:
- 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.
Now that list might seem a bit daunting to most politicians, but the article explains each concept well. Let’s hope it gains some traction in media circles as well as in politics – it’s sorely needed.