Computational Bayesian Statistics - STATS326 (2022)

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: 50:50

Trimesters and Locations

Occurrence Code When taught Where taught
22B (HAM)B Trimester : 18 Jul 2022 - 13 Nov 2022 Hamilton

Timetabled Lectures

The Timetable for 2022 is not available.


Indicative Fees

Fees for 2022 are not yet available.


Paper Outlines

The following 2021 paper outlines are available for STATS326. Please contact the Faculty or School office for details on 2022 outlines.

Additional Information

Available Subjects:  Data Analytics | Statistics

Other available years: Computational Bayesian Statistics - STATS326 (2021) , Computational Bayesian Statistics - STATS326 (2020) , Computational Bayesian Statistics - STATS326 (2019)

Paper details current as of : 16 September 2021 6:58pm
Indicative fees current as of : 17 September 2021 4:30am

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