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| 베이지안 카이제곱 검정× | 베이즈 독립표본 t-검정× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1967 | 2009 (modern form); 1961 (Jeffreys prior framework) |
| 창시자≠ | I. J. Good; extended by Gunel, Dickey, and Wagenmakers et al. | Harold Jeffreys (foundational); operationalized by Rouder et al. |
| 유형≠ | Bayesian nonparametric association test | Bayesian hypothesis test |
| 원전≠ | 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 ↗ | Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16(2), 225–237. DOI ↗ |
| 별칭 | Bayesian contingency table test, Bayes factor chi-square, Bayesian goodness-of-fit test, Bayesian association test | Bayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-test |
| 관련 | 3 | 3 |
| 요약≠ | 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 Bayesian independent samples t-test quantifies evidence for or against a mean difference between two independent groups using a Bayes factor rather than a p-value. Rooted in Jeffreys's probability framework and popularized by Rouder et al. (2009), it places a Cauchy prior on the standardized effect size and returns continuous evidence for both the null and alternative hypotheses. |
| ScholarGate데이터셋 ↗ |
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