This entry defines nonsignificance within the context of null hypothesis significance testing (NHST), the dominant scientific statistical method for making inferences about populations based on sample data. Emphasis is placed on the three routes to nonsignificance: a real lack of effect in the population; failure to detect a real effect because of an insufficiently large sample; or failure to detect a real effect because of a methodological flaw. Of greatest importance is the recognition that nonsignificance is not affirmative evidence of the absence of an effect in the population.

Nonsignificance is the determination in NHST that no statistically significant effect (e.g., correlation, difference between means, and dependence of proportions) can be inferred for a population. NHST typically involves statistical testing (e.g., t test) performed on a ...

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