Linganisha mbinu

	Takwimu za Kuelezea za Kibayesiani	Kipimo cha t cha sampuli huru za Kibayesiani
Nyanja	Takwimu	Takwimu
Familia	Hypothesis test	Hypothesis test
Mwaka wa asili	1763/1812	2009 (modern form); 1961 (Jeffreys prior framework)
Mwanzilishi	Thomas Bayes / Pierre-Simon Laplace	Harold Jeffreys (foundational); operationalized by Rouder et al.
Aina	Bayesian parameter estimation	Bayesian hypothesis test
Chanzo asilia	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	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.
Majina mbadala	Bayesian summaries, posterior descriptives, Bayesian parameter estimation, credible-interval summaries	Bayesian two-sample t-test, Bayes factor t-test, JZS t-test, Bayesian unpaired t-test
Zinazohusiana	5	3
Muhtasari	Bayesian 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.