Studying online

There are now 2 possible online modes for units:

Units with modes Online timetabled and Online flexible are available for any student to self-enrol and study online.

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Unit Overview

Description

This unit introduces fundamental concepts of Bayesian statistics and illustrates how to apply them to various areas of scientific research. Probabilistic programming languages (WinBugs, JAGS and/or Stan) are introduced, and their interfaces to the statistical computing and graphics environment R are discussed. These languages 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.

Credit
6 points
Offering
(see Timetable)
AvailabilityLocationMode
Semester 2UWA (Perth)Face to face
Details for undergraduate courses
  • Level 3 core unit in the Data Science major sequence
  • Level 3 option in the Statistics major sequence
  • Level 3 elective
Outcomes

Students are able to (1) understand basic concepts of Bayesian statistics; (2) fit Bayesian models to their data using modern probabilistic programming languages; (3) critically assess fitted models; and (4) interpret and communicate results of Bayesian data analyses.

Assessment

Indicative assessments in this unit are as follows: (1) assignments; (2) in-semester tests; and (3) a final examination. Further information is available in the unit outline.



Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)
Associate Professor Berwin Turlach
Unit rules
Prerequisites

Course Enrolment in
the MJD-DATSC Data Science major
or the MJD-QTMTD Quantitative Methods major
and STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT4066 Bayesian Computing and Statistics
Contact hours
Lectures: 2-hours per week
Computer Labs: 2-hours per week
Note
STAT3405 will be offered in Semester 2 from 2022.
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
  • All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
  • Unit readings, including any essential textbooks, are listed in the unit outline for each unit, one week prior the commencement of study. The unit outline will be available via the LMS and the UWA Handbook one week prior the commencement of study. Reading lists and essential textbooks are subject to change each semester. Information on essential textbooks will also be made available on the Essential Textbooks. This website is updated regularly in the lead up to semester so content may change. It is recommended that students purchase essential textbooks for convenience due to the frequency with which they will be required during the unit. A limited number of textbooks will be made available from the Library in print and will also be made available online wherever possible. Essential textbooks can be purchased from the commercial vendors to secure the best deal. The Student Guild can provide assistance on where to purchase books if required. Books can be purchased second hand at the Guild Secondhand bookshop (second floor, Guild Village), which is located on campus.
  • Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.