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: 50:50
Restriction(s): STAT326

Semesters and Locations

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

Timetabled Lectures

The Timetable for 2020 is not available.


Indicative Fees

Fees for 2020 are not yet available.


Paper Outlines

The following 2019 paper outlines are available for STATS326. Please contact the Faculty or School office for details on 2020 outlines.

Additional Information

Available Subjects:  Data Analytics | Statistics

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

Paper details current as of : 16 August 2019 9:46am
Indicative fees current as of : 29 July 2019 3:04pm

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