Ellis, Andrew (26 April 2019). Introduction to Bayesian statistics (Unpublished). In: Decision making in risky situations (Course for the Doctoral Program for Cognition, Learning, and Memory). Bern. 26.04.2019.
In this workshop, I will provide an introduction to the Bayesian paradigm for data analysis, focusing on both parameter estimation and hypothesis testing. After discussing theoretical aspects of Bayesian inference, I will provide a hands-on tutorial, in which we will consider a traditional t-test from a Bayesian perspective. We will first learn how to estimate Bayes factors using Jasp, an open- source statistical software package targeted at novice users. We will then look at how to perform the same analysis using Jasp’s underlying R package (BayesFactor), and I will show how to implement traditional tests a general linear models using the brms package in R. Finally, I will discuss potential limitations of relying on Bayes factors, and how to overcome these limitations by adopting a principled workflow for building and evaluating probabilistic models in Bayesian inference.
Following this workshop will enable participants to interpret and critically read research articles using Bayesian statistics. Furthermore, participants will be introduced to using JASP and R, and they should be able perform their own Bayesian analyses using these programs.
Item Type: |
Conference or Workshop Item (Speech) |
|---|---|
Division/Institute: |
07 Faculty of Human Sciences > Institute of Psychology > Cognitive Psychology, Perception and Methodology |
Graduate School: |
Swiss Graduate School for Cognition, Learning and Memory (SGS-CLM) |
UniBE Contributor: |
Ellis, Andrew |
Subjects: |
100 Philosophy > 150 Psychology |
Language: |
English |
Submitter: |
Andrew William Ellis |
Date Deposited: |
19 May 2020 11:09 |
Last Modified: |
05 Dec 2022 15:38 |
Additional Information: |
Workshop: Using Bayesian statistics |
URI: |
https://boris.unibe.ch/id/eprint/142740 |
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