방법 비교

	베이즈 요인 분산 분석	베이지안 t-검정
분야	통계학	베이지안
계열	Hypothesis test	Bayesian methods
기원 연도	1961 (foundations); 2012 (default Bayes factor formulation)	2009
창시자	Harold Jeffreys (foundational); modern default-prior form by Jeffrey N. Rouder et al.	Rouder, Speckman, Sun, Morey & Iverson
유형	Bayesian hypothesis test	Bayesian hypothesis test
원전	Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374.	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.
별칭	Bayesian factorial ANOVA, Bayes factor two-way ANOVA, Bayesian 2×k ANOVA, Bayesian two-factor ANOVA	bayesian two-sample t-test, bayes factor t-test, Bayesçi t-Testi
관련	4	5
요약	Bayesian two-way ANOVA extends the classical two-way analysis of variance by replacing p-values with Bayes factors and posterior distributions. It quantifies evidence for or against main effects and their interaction using prior-weighted model comparison, yielding conclusions that are directly interpretable in probabilistic terms rather than relying on a fixed significance threshold.	The Bayesian t-test, formalised by Rouder and colleagues in 2009, is a two-group comparison method that works within a Bayesian framework. Instead of a p-value, it produces a Bayes Factor (BF₁₀) that quantifies the evidence the data provide for the alternative hypothesis relative to the null, and it reports the full posterior distribution of the standardised effect size δ with a highest-density interval.