Comparer des méthodes

	Analyse bayésienne de tableaux croisés	Test du Khi-deux d'indépendance
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1974	1900
Auteur d'origine	Gunel & Dickey	Karl Pearson
Type	Bayesian association test	Nonparametric test of association
Source fondatrice	Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557.	Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175.
Alias	Bayesian chi-square test, Bayesian contingency table test, Bayes factor association test, Bayesian crosstab analysis	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Apparentées	4	2
Résumé	Bayesian cross-tabulation analysis tests whether two categorical variables are associated by computing a Bayes factor that quantifies the evidence for an association model against an independence model. Unlike classical chi-square testing, it provides a continuous measure of evidence, supports the null hypothesis directly, and updates naturally with prior knowledge about the cell probabilities.	The chi-square test of independence is a nonparametric hypothesis test that examines whether two categorical variables are associated by comparing observed and expected frequencies in a cross-tabulation. It rests on the chi-square criterion introduced by Karl Pearson in 1900.