| Literature DB >> 28378250 |
Alexander Etz1, Joachim Vandekerckhove2.
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/ .Keywords: Bayesian inference and parameter estimation; Bayesian statistics; Tutorial
Mesh:
Year: 2018 PMID: 28378250 DOI: 10.3758/s13423-017-1262-3
Source DB: PubMed Journal: Psychon Bull Rev ISSN: 1069-9384