Hypothesis testClassical statistics

Bayesian Chi-Square Test

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'.

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Sources

  1. Good, I. J. (1967). A Bayesian significance test for multinomial distributions. Journal of the Royal Statistical Society: Series B (Methodological), 29(3), 399–418. DOI: 10.1111/j.2517-6161.1967.tb00707.x
  2. Jamil, T., Ly, A., Morey, R. D., Love, J., Marsman, M., & Wagenmakers, E.-J. (2017). Default 'Gunel and Dickey' Bayes factors for contingency tables. Behavior Research Methods, 49(2), 638–652. DOI: 10.3758/s13428-016-0739-8

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Referenced by

ScholarGateBayesian chi-square test (Bayesian Chi-Square Test of Independence). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/bayesian-chi-square-test