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Estadística Descriptiva Bayesiana×Prueba t bayesiana para muestras independientes×
CampoEstadísticaEstadística
FamiliaHypothesis testHypothesis test
Año de origen1763/18122009 (modern form); 1961 (Jeffreys prior framework)
Autor originalThomas Bayes / Pierre-Simon LaplaceHarold Jeffreys (foundational); operationalized by Rouder et al.
TipoBayesian parameter estimationBayesian hypothesis test
Fuente seminalGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Rouder, 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 ↗
AliasBayesian summaries, posterior descriptives, Bayesian parameter estimation, credible-interval summariesBayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-test
Relacionados53
ResumenBayesian descriptive statistics summarizes data by combining observed information with prior knowledge through Bayes' theorem, yielding posterior distributions over parameters such as the mean and variance. Instead of point estimates and p-values, results are expressed as posterior means, medians, and credible intervals that carry a direct probability interpretation.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.
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ScholarGateComparar métodos: Bayesian descriptive statistics · Bayesian Independent Samples t-test. Recuperado el 2026-06-17 de https://scholargate.app/es/compare