Statistical significance evaluates whether an observed effect is unlikely under a null hypothesis. It does not automatically mean the effect is large or important in the real world.
Practical significance considers effect size, cost, risk, and context. A tiny effect can be statistically significant in a large dataset but irrelevant for decisions.
Good reporting includes confidence intervals, effect sizes, and clear discussion of what the results do and do not imply.
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