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.
Course learning outcomes
- Critically compare frequentist and Bayesian approaches for the same model type
- Use Bayesian workflow to interrogate and validate model output
- Explain the benefits and weakness of partial pooling
- Experiment with different priors and critically evaluate results
- Identify an appropriate model comparison technique and interpret the results for an application
Fee calculator
To display course fees, please select your status and program below:
We’re updating this Fee Calculator. It currently shows fees for programs only. Please check the relevant program for full fee details.
Study Abroad student tuition fees are available here.
Only some Postgraduate Coursework programs are available as Commonwealth Supported. Please check your program for specific fee information.
The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.