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 be mislead
Extrapolating beyond the data is risky
Beware of the base-rate - the ability of an imperfect test to identify a condition depends upon the likelihood of that condition occurring (the base rate)
Controls are important
Randomization avoids bias
Seek replication, not pseudoreplication
Scientists are human
Significance is significant
Seperate no effect from non-significance
Effect size matters
Study relevance limits generalizations
Feelings influence risk perception
Dependencies change risks
Data can be dredged or cherry picked
Extreme measurements may mislead
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