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.
|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)
|Tue||2:00 PM||4:00 PM||G.3.33||Jul 12 - Oct 17|
|Thu||3:00 PM||4:00 PM||G.3.33||Jul 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)
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.
Paper details current as of : 10 January 2022 12:10pm
Indicative fees current as of : 22 January 2022 4:30am