Computational Bayesian Statistics - STATS326 (2020)

Bayesian approach has the potential to model any complex real life problem. In practice, Bayesian methods are implemented using various computational algorithms. This paper introduces the basics of some of the most widely used computational methods, viz the ABC method and the MCMC methods.

Paper Information

Points: 15.0
Prerequisite(s): STAT221 or STATS221 or STAT226 or STATS226 or at the discretion of the Paper Convenor.
Internal assessment / examination: 100:0
Restriction(s): STAT326

Trimesters and Locations

Occurrence Code When taught Where taught
20B (HAM)B Trimester : 13 Jul 2020 - 8 Nov 2020 Hamilton

Timetabled Lectures for Computational Bayesian Statistics (STATS326)

DayStartEndRoomDates
Tue2:00 PM4:00 PMG.3.33Jul 13 - Oct 18
Thu3:00 PM4:00 PMG.3.33Jul 13 - Oct 18

NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for STATS326 for more details


Indicative Fees for Computational Bayesian Statistics (STATS326)

Occurrence Domestic International
 Tuition Resource 
20B (HAM) $780 $0 $3145
You will be sent an enrolment agreement which will confirm your fees.
Tuition fees shown below are indicative only and may change. There are additional fees and charges related to enrolment - please see the Table of Fees and Charges for more information.

Paper Outlines for Computational Bayesian Statistics (STATS326)

The following paper outlines are available for Computational Bayesian Statistics (STATS326).
If your paper occurrence is not listed contact the Faculty or School office.

Additional Information

Available Subjects:  Data Analytics | Statistics

Other available years: Computational Bayesian Statistics - STATS326 (2021) , Computational Bayesian Statistics - STATS326 (2019)

Paper details current as of : 23 October 2020 11:20am
Indicative fees current as of : 16 October 2020 12:49pm

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