Comparer des méthodes

	Analyse de la taille d'effet	Test t pour échantillons indépendants
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1969 (first edition); 1988 (definitive second edition)	1908
Auteur d'origine	Jacob Cohen	Student (W. S. Gosset)
Type	Standardized magnitude estimation	Parametric mean comparison
Source fondatrice	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Student (W. S. Gosset) (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Alias	effect magnitude estimation, standardized effect measure, practical significance analysis, ES analysis	two-sample t-test, unpaired t-test, Student t-test, independent groups t-test
Apparentées	4	4
Résumé	Effect size analysis quantifies the practical magnitude of a statistical result independently of sample size. Rather than asking only whether a difference or relationship is statistically significant, it asks how large it is, using standardized indices such as Cohen's d, eta-squared, omega-squared, or Pearson's r that allow direct comparison across studies and populations.	The independent samples t-test is a parametric hypothesis test that determines whether the means of two independent, unrelated groups differ significantly on a continuous outcome variable. Derived from Gosset's 1908 t-distribution, it is one of the most widely used inferential tests in social, behavioral, biomedical, and experimental sciences.