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Bayesův t-test pro nezávislé výběry×Nezávislý t-test×
OborStatistikaStatistika
RodinaHypothesis testHypothesis test
Rok vzniku2009 (modern form); 1961 (Jeffreys prior framework)1908
TvůrceHarold Jeffreys (foundational); operationalized by Rouder et al.Student (W. S. Gosset)
TypBayesian hypothesis testParametric mean comparison
Původní zdrojRouder, 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 ↗Student (W. S. Gosset) (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
Další názvyBayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-testtwo-sample t-test, unpaired t-test, Student t-test, independent groups t-test
Příbuzné34
ShrnutíThe 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.The independent samples t-test is a parametric hypothesis test that determines whether the means of two independent, unrelated groups differ significantly on a continuous outcome variable. Derived from Gosset's 1908 t-distribution, it is one of the most widely used inferential tests in social, behavioral, biomedical, and experimental sciences.
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ScholarGatePorovnat metody: Bayesian Independent Samples t-test · Independent samples t-test. Získáno 2026-06-18 z https://scholargate.app/cs/compare