Comparer des méthodes

	Test du Chi-carré Bayésien	Bayesian Fisher's exact test
Domaine	Statistique	Statistique
Famille	Hypothesis test	Hypothesis test
Année d'origine	1967	1974 (Bayesian form); 1935 (Fisher's exact test)
Auteur d'origine	I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al.	Gunel & Dickey (Bayesian form); R. A. Fisher (classical exact test)
Type	Bayesian nonparametric association test	Bayesian hypothesis test for independence
Source fondatrice	Good, I. J. (1967). A Bayesian significance test for multinomial distributions. Journal of the Royal Statistical Society: Series B (Methodological), 29(3), 399–418.	Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557.
Alias	Bayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test	Bayesian exact test for independence, Bayesian contingency table test, Bayes factor Fisher test, BFexact
Apparentées	3	4
Résumé	The Bayesian chi-square test evaluates independence or goodness-of-fit in frequency tables using Bayes factors rather than classical p-values. It quantifies evidence for or against an association between categorical variables, updating prior beliefs with observed counts and delivering an odds-like ratio that distinguishes 'no evidence' from 'evidence of no effect'.	The Bayesian Fisher's exact test evaluates independence between two categorical variables in a 2x2 table by computing a Bayes factor rather than a p-value. Using conjugate priors on cell probabilities — most commonly the Gunel-Dickey framework — it quantifies how much the observed data favor an association model over an independence model, providing a continuous scale of evidence in both directions.