Lecture 26 of the Sports Biomechanics Lecture Series #SportsBiomLS
Tony Myers presents an overview of Bayesian statistics for sport and exercise science, including intuitive examples and demonstrations.
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00:00 Sports Biomechanics Lecture Series
01:15 Presentation Aims
02:14 Issues Identified With Traditional Statistical Approaches
03:17 What are the Alternative Statistical Approaches?
03:42 The Benefits of Bayesian Data Analysis
05:50 The Basis of Inferential Statistics
06:56 What is Bayesian Inference?
07:18 What is a Bayes Factor?
10:46 Bayesian Parameter Estimation
11:20 Bayesian Posterior Probability
12:46 Bayesian Credible Intervals
18:35 Bayesian Analysis in JASP
19:58 Interpreting Bayesian JASP Outputs
23:42 Software for Bayesian Analysis
25:14 Bayesian Analysis Workflow
31:21 Diagnostic Checks for Bayesian Analysis
34:00 Comparing Models Using Bayesian Methods
42:50: Bayesian Statistics: Summary
44:10 Q&A (Getting Started, Using JASP, Making Inferences, Prior Distributions, Small Samples, Multiple Comparisons, and More)
Some useful links from the Bayesian Sport Science lecture:
2016 ASA Statement: [ Ссылка ]
The American Statistician Editorial 2019: [ Ссылка ]
The American Statistician Special Issue: [ Ссылка ]
Some examples of sport science studies using Bayesian statistics (with Tony as an author):
Myers et al., 2020 (Swimming): [ Ссылка ]
Dugdale et al., 2020 (Soccer): [ Ссылка ]
Cullen et al., 2019 (Sleep): [ Ссылка ]
Ellis et al., 2019 (Caffeine / Soccer): [ Ссылка ]
Web: [ Ссылка ]
Audio: [ Ссылка ]
Twitter: [ Ссылка ]
Monthly research newsletter: [ Ссылка ]
