Vertaile menetelmiä

	Bayesiläinen lineaarinen regressio	Riippumattomien otosten t-testi
Tieteenala	Bayesilainen tilastotiede	Tilastotiede
Menetelmäperhe	Bayesian methods	Hypothesis test
Syntyvuosi	2013 (modern reference); foundations 18th–19th century	1908
Kehittäjä	Thomas Bayes / Pierre-Simon Laplace (foundations); modern workflow codified by Gelman et al.	Student (W. S. Gosset)
Tyyppi	Bayesian linear model	Parametric mean comparison
Alkuperäislähde	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.
Rinnakkaisnimet	bayesian linear model, probabilistic linear regression, Bayesçi Doğrusal Regresyon	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Liittyvät	4	4
Tiivistelmä	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.