方法对比

	贝叶斯卡方检验	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	1967	1900
提出者	I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al.	Karl Pearson
类型	Bayesian nonparametric association test	Nonparametric test of association
开创性文献	Good, I. J. (1967). A Bayesian significance test for multinomial distributions. Journal of the Royal Statistical Society: Series B (Methodological), 29(3), 399–418.	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 contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test	chi-squared test, Pearson's chi-square test, test of independence, ki-kare bağımsızlık testi
相关	3	2
摘要	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 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.