方法对比

	贝叶斯费舍尔精确检验	卡方独立性检验
领域	统计学	统计学
方法族	Hypothesis test	Hypothesis test
起源年份	1974 (Bayesian form); 1935 (Fisher's exact test)	1900
提出者	Gunel & Dickey (Bayesian form); R. A. Fisher (classical exact test)	Karl Pearson
类型	Bayesian hypothesis test for independence	Nonparametric test of association
开创性文献	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.
别名	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
相关	4	2
摘要	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.