STAT4066 Bayesian Computing and Statistics

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 1UWA (Perth)Face to face
Content
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.
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.
Assessment
Typically this unit is assessed in the following ways: (1) assignments; (2) in-semester tests; and (3) a final examination. Further information is available in the unit outline.

Supplementary assessment is only available in this unit in the case of a student who has obtained a mark of 45 to 49 and is currently enrolled in this unit, and it is the only remaining unit that the student must pass in order to complete their course
Unit Coordinator(s)
Associate Professor Berwin Turlach
Unit rules
Prerequisites:
STAT1400 Statistics for Science;
or
STAT1520 Economic and Business Statistics;
or
MATH1002 Mathematical Methods 2;
or
MATH1020 Calculus, Probability and Statistics;
or
MATH1020 Calculus, Probability and Statistics
Incompatibility:
STAT3405 Introduction to Bayesian Computing and Statistics
Contact hours
lectures: 2 hours per week; computer labs: 3 hours per fortnight; tutorials: 1 hour per fortnight
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  • Books and other material wherever listed may be subject to change. Book lists relating to 'Preliminary reading', 'Recommended reading' and 'Textbooks' are, in most cases, available at the University Co-operative Bookshop (from early January) and appropriate administrative offices for students to consult. Where texts are listed in the unit description above, an asterisk (*) indicates that the book is available in paperback.