There is Nothing Magical About Bayesian Statistics: An Introduction to Epistemic Probabilities in Data Analysis for Psychology Starters
Détails
Etat: Public
Version: Author's accepted manuscript
Licence: Non spécifiée
ID Serval
serval:BIB_C4C075D72C08
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
There is Nothing Magical About Bayesian Statistics: An Introduction to Epistemic Probabilities in Data Analysis for Psychology Starters
Périodique
Basic and Applied Social Psychology
Statut éditorial
Publié
Date de publication
25/07/2020
Peer-reviewed
Oui
Volume
42
Numéro
6
Pages
387-412
Langue
anglais
Résumé
This paper is a reader-friendly introduction to Bayesian inference applied to psychological science. We begin by explaining the difference between frequentist and epistemic interpretations of probability that underpin respectively frequentist and Bayesian statistics. We use a concrete example – a student wondering whether s/he carries the virus statisticus malignum – to explain how both approaches are different one from another. We illustrate Bayesian inference with intuitive examples, before introducing the mathematical framework. Different schools of thoughts and recommendations are discussed to illustrate how to use priors in Bayes Factor testing. We discuss how psychology could benefit from a greater reliance on Bayesian methods. Finally, we illustrate how to compute Bayes Factors analyses with real data and provide the R code.
Mots-clé
Bayesian statistics, probability, Bayes Factor, statistical inference
Création de la notice
30/06/2020 21:16
Dernière modification de la notice
22/08/2020 7:10