Comparer des méthodes

	Test de Wilcoxon bilatéral bayésien	Test t pour échantillons appariés
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	2014–2017	1908
Auteur d'origine	Benavoli, Corani, Mangili, and colleagues	Student (W. S. Gosset)
Type	Bayesian nonparametric paired test	Parametric mean comparison
Source fondatrice	Benavoli, A., Corani, G., & Mangili, F. (2014). Should we really use post-hoc tests based on mean-ranks? Journal of Machine Learning Research, 17(5), 1–10.	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Alias	Bayesian signed-rank test, Bayesian nonparametric paired comparison, Benavoli signed-rank Bayesian test, signed-rank Bayesian hypothesis test	dependent t-test, matched pairs t-test, repeated measures t-test, within-subjects t-test
Apparentées	2	3
Résumé	The Bayesian Wilcoxon signed-rank test is a Bayesian nonparametric method for comparing two paired or related samples. Rather than returning a single p-value, it produces posterior probabilities that one condition is better, practically equivalent, or worse than the other, enabling richer and more interpretable inference for paired continuous or ordinal data without assuming normality.	The paired samples t-test is a parametric hypothesis test that compares the means of two related measurements from the same subjects or matched pairs to determine whether the average difference is significantly different from zero. It leverages the dependency between observations to produce a more powerful test than its independent-samples counterpart.