title: Introduction to Bayesian Inference for Psychology.
abstract: We introduce the fundamental tenets of Bayesian inference, which derive from two basic laws of probability theory. We cover the interpretation of probabilities, discrete and continuous versions of Bayes' rule, parameter estimation, and model comparison. Using seven worked examples, we illustrate these principles and set up some of the technical background for the rest of this special issue of Psychonomic Bulletin & Review. Supplemental material is available via https://osf.io/wskex/ .
authors.affiliation: University of California, Irvine, CA, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Etz
authors.affiliation: University of California, Irvine, CA, USA. joachim@uci.edu.
authors.forename: Joachim
authors.initials: J
authors.lastname: Vandekerckhove
mesh_terms: D001499:Bayes Theorem; D006801:Humans; D011338:Probability Theory; D011584:Psychology
keywords: Bayesian inference and parameter estimation; Bayesian statistics; Tutorial