Comparer des méthodes

	Effect Size in Education Research	Taille de l'effet
Domaine	Education	Statistiques de recherche
Famille	Process / pipeline	Process / pipeline
Année d'origine	1988	1988
Auteur d'origine	Statistical methodology (Cohen; Glass; Hedges & Olkin) applied in education	Jacob Cohen
Type	Standardized index of the magnitude of an effect or difference	Concept
Source fondatrice	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 9780805802832	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 0-8058-0283-5
Alias	Educational Effect Size, Standardized Mean Difference in Education, Hedges' g in Education, Effect Size Reporting	ES, Cohen's d, standardized effect, practical significance
Apparentées	2	4
Résumé	An effect size is a standardized, scale-free measure of the magnitude of a difference or relationship — how big an effect is, not just whether it is statistically significant. In education research it is the common currency for reporting intervention impacts and for combining studies in meta-analysis, with the standardized mean difference (Cohen's d, or its bias-corrected form Hedges' g) the most familiar. Effect sizes let researchers compare effects across studies, outcomes, and scales, and translate statistical results into terms practitioners can weigh.	Effect size quantifies the magnitude of a research finding independent of sample size. While a p-value tells you whether a result is statistically significant, an effect size tells you how big the result is. Jacob Cohen formalized effect size measurement in behavioral sciences (1988), establishing standard benchmarks (small = 0.2, medium = 0.5, large = 0.8 for Cohen's d). Effect sizes are essential for meta-analysis, power analysis, and communicating the practical importance of research findings.