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	Bayesiansk exakt Fishertest	Chi-två-test för oberoende
Ämnesområde	Statistik	Statistik
Familj	Hypothesis test	Hypothesis test
Ursprungsår	1974 (Bayesian form); 1935 (Fisher's exact test)	1900
Upphovsperson	Gunel & Dickey (Bayesian form); R. A. Fisher (classical exact test)	Karl Pearson
Typ	Bayesian hypothesis test for independence	Nonparametric test of association
Ursprungskälla	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 exact test for independence, Bayesian contingency table test, Bayes factor Fisher test, BFexact	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
Närliggande	4	2
Sammanfattning	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.	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.