Computational Bayesian Statistics - STATS326 (2021)

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): STATS221 or STATS222 or STATS226 or by the permission of the Chairperson of Department.
Internal assessment / examination: 70:30

Trimesters and Locations

Occurrence Code When taught Where taught
21B (HAM)B Trimester : 12 Jul 2021 - 7 Nov 2021 Hamilton

Timetabled Lectures for Computational Bayesian Statistics (STATS326)

Tue2:00 PM4:00 PMG.3.33Jul 12 - Oct 17
Thu3:00 PM4:00 PMG.3.33Jul 12 - Oct 17

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 
21B (HAM) $789 $3239
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 (2022) , Computational Bayesian Statistics - STATS326 (2020) , Computational Bayesian Statistics - STATS326 (2019)

Paper details current as of : 10 January 2022 12:10pm
Indicative fees current as of : 22 January 2022 4:30am

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