Effect size

Effect size is a quantitative measure of how big a difference or relationship is, expressed in a way that's independent of sample size. Statistical significance tells you whether an effect is likely real; effect size tells you whether it's big enough to care about.

Common effect-size metrics in psychology include Cohen's d (for differences between groups), Pearson's r (for correlations), and odds ratios. In assessment, effect sizes are reported for how much scores change after an intervention, or how strongly two measures correlate. Conventional benchmarks ("small," "medium," "large") exist but should be interpreted in context — what's small in one field can be big in another.