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领域统计学统计学
方法族Bayesian methodsHypothesis test
起源年份17631908
提出者Thomas Bayes; Pierre-Simon LaplaceStudent (W. S. Gosset)
类型Probabilistic inference paradigmParametric mean comparison
开创性文献Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418. link ↗Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
别名Bayes inference, Bayesian statistics, Bayesian updating, posterior inferencestudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
相关34
摘要Bayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités.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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ScholarGate方法对比: Bayesian Inference · Independent t-test. 于 2026-06-18 检索自 https://scholargate.app/zh/compare