Sammenlign metoder

	Bayesiansk lineær regression	Uafhængig stikprøve t-test
Fagområde	Bayesiansk	Statistik
Familie	Bayesian methods	Hypothesis test
Oprindelsesår	2013 (modern reference); foundations 18th–19th century	1908
Ophavsperson	Thomas Bayes / Pierre-Simon Laplace (foundations); modern workflow codified by Gelman et al.	Student (W. S. Gosset)
Type	Bayesian linear model	Parametric mean comparison
Oprindelig kilde	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	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Aliasser	bayesian linear model, probabilistic linear regression, Bayesçi Doğrusal Regresyon	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Relaterede	4	4
Resumé	Bayesian 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.