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unitinfo
This page provides helpful information about many coursework units offered by
Computer Science and Software Engineering
in 2023.
The information here is not official -
for official information please see the
current UWA Handbook.
Instead, it will help students to prepare for their future units,
before the beginning of each semester,
and before they have access to
UWA's
Learning Management System (LMS).
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About the unit STAT4066 Bayesian Computing and Statistics (2nd semester 2023)
Unit description:
This unit introduces concepts of Bayesian statistics and illustrates how to apply them to various areas of scientific research. Self-implemented algorithms and probabilistic programming languages (WinBugs, JAGS and/or Stan) are introduced, and the interfaces of the latter to the statistical computing and graphics environment R are discussed. Some computational aspects underlying these probabilistic programming languages are discussed to justify the framework of these algorithms. The algorithms are used, either directly or via their R interface, to fit statistical models within a Bayesian framework to real-world examples from many disciplines such as engineering, science (e.g. agricultural, biological, environmental, medical and physical), social sciences, economics, finance and astronomy.
Unit outcomes:
Students are able to (1) understand concepts of Bayesian statistics; (2) fit Bayesian models to their data using modern probabilistic programming languages; (3) implementation of standard Bayesian models from first principles; (4) critically assess fitted models; and (5) interpret and communicate results of Bayesian data analyses.
Unit coordinator:
Unit homepage:
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Unit is offered in these majors and courses:
Indicative weekly topics:
| week 1 |
Probability theory |
| week 2 |
Probability theory |
| week 3 |
One parameter models |
| week 4 |
One parameter models |
| week 5 |
One and multiparameter models |
| week 6 |
Priors and regression models |
| week 7 |
Graphical models and posterior predictive distribution |
| week 8 |
Regression and posterior predictive checks |
| week 9 |
Regression models |
| week 10 |
Generalised linear models |
| week 11 |
Hierarchical modelling |
| week 12 |
Hierarchical modelling |
Indicative assessment:
Computer Labs, Assignments, Take Home Exam
Operating system(s) used in this unit:
Different units will use different operating systems for their teaching - for in-class examples, laboratory exercises, and programming projects.
If an operating system is REQUIRED, it will be used when marking assessments.
ANY reasonable platform
This information last updated 6:46pm Thu 20th Apr 2023
