Why report effect size alongside p-values?
easyAnswer
- P-values conflate signal size with sample size — huge n makes trivial effects significant.
- Effect size quantifies practical importance regardless of n.
- Common measures: Cohen's d (standardized mean difference: 0.2 small, 0.5 medium, 0.8 large); odds ratio / relative risk (binary outcomes); Pearson ; Cliff's delta (non-parametric).
- Always report effect size with CIs and p-values.
Check yourself — multiple choice
- P-values alone suffice
- P-values conflate effect and n; effect size (Cohen's d, OR, r) quantifies practical importance regardless of n
- Never report
- Only for regression
Effect size: quantifies practical significance independently of n.
#hypothesis-testing#power
Practise Statistics Fundamentals
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