Bayesian Statistical Practice

Undergraduate | 2026

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Area/Catalogue
STAT 3012
Course ID icon
Course ID
204955
Level of study
Level of study
Undergraduate
Unit value icon
Unit value
6
Course level icon
Course level
3
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

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

Prerequisite(s)

  • Must have completed STAT2900

Corequisite(s)

N/A

Antirequisite(s)

N/A

Assessment

N/A

Degree list
The following degrees include this course
Study Bachelor of Mathematics at Adelaide University - Information for Domestic students