Course overview
Bayesian statistics is a powerful framework for statistical analysis. This course will introduce students to this framework by building on previous knowledge of generalised linear modelling with a Bayesian perspective. Learners will gain skills in Bayesian workflow and more advanced modelling tools like mixed effects models, with computational details reinforced in subsequent courses.
- Bayesian Thinking
- Bayesian Workflow
- Bayesian Practice
Course learning outcomes
- Critically compare frequentist and Bayesian approaches for the same model type
- Apply analytic and computational approaches to Bayesian problems and identify which is most appropriate in a particular use case.
- Use Bayesian workflow to interrogate and validate model output
- Explain the benefits and weakness of hierarchical modelling
- Experiment with different priors and critically evaluate results
- Identify an appropriate model comparison technique and interpret the results for an application
Availability
Class details
Adelaide City Campus East
Group 1
Class number 26142
Section FR01
Size 100
Available 94
Class number 26143
Section PR04
Size 25
Available 25
Class number 26144
Section PR03
Size 25
Available 23
Class number 26145
Section PR02
Size 25
Available 24
Class number 26146
Section PR01
Size 25
Available 22
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