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베이즈 선형 회귀×독립 표본 t-검정×
분야베이지안통계학
계열Bayesian methodsHypothesis test
기원 연도2013 (modern reference); foundations 18th–19th century1908
창시자Thomas Bayes / Pierre-Simon Laplace (foundations); modern workflow codified by Gelman et al.Student (W. S. Gosset)
유형Bayesian linear modelParametric mean comparison
원전Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
별칭bayesian linear model, probabilistic linear regression, Bayesçi Doğrusal Regresyonstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
관련44
요약Bayesian linear regression is a probabilistic extension of the ordinary linear model, introduced through Bayes' rule and formalised in its modern computational workflow by Gelman et al. (2013). Rather than returning a single point estimate for each coefficient, it combines a user-specified prior distribution with the likelihood of the observed data to produce a full posterior distribution over all parameters, from which credible intervals and posterior predictive distributions are derived.The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.
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