Salīdzināt metodes

	Beijesiskā inference	Neatkarīgo paraugu t-tests
Nozare	Statistika	Statistika
Saime	Bayesian methods	Hypothesis test
Izcelsmes gads	1763	1908
Autors	Thomas Bayes; Pierre-Simon Laplace	Student (W. S. Gosset)
Tips	Probabilistic inference paradigm	Parametric mean comparison
Pirmavots	Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418.	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.
Citi nosaukumi	Bayes inference, Bayesian statistics, Bayesian updating, posterior inference	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
Saistītās	3	4
Kopsavilkums	Bayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités.	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.