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| 베이즈 피셔 정확 검정(Bayesian Fisher's Exact Test)× | 베이지안 카이제곱 검정× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1974 (Bayesian form); 1935 (Fisher's exact test) | 1967 |
| 창시자≠ | Gunel & Dickey (Bayesian form); R. A. Fisher (classical exact test) | I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al. |
| 유형≠ | Bayesian hypothesis test for independence | Bayesian nonparametric association test |
| 원전≠ | Gunel, E., & Dickey, J. (1974). Bayes factors for independence in contingency tables. Biometrika, 61(3), 545–557. DOI ↗ | 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 ↗ |
| 별칭 | Bayesian exact test for independence, Bayesian contingency table test, Bayes factor Fisher test, BFexact | Bayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test |
| 관련≠ | 4 | 3 |
| 요약≠ | 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 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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