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.
|Prerequisite(s):||STAT221 or STATS221 or STAT226 or STATS226 or at the discretion of the Paper Convenor.|
|Internal assessment / examination:||50:50|
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)
|Tue||2:00 PM||4:00 PM||G.3.33||Jul 13 - Oct 18|
|Thu||3:00 PM||4:00 PM||G.3.33||Jul 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)
The following 2019 paper outlines are available for STATS326. Please contact the Faculty or School office for details on 2020 outlines.
Other available years: Computational Bayesian Statistics - STATS326 (2019)
Paper details current as of : 20 March 2020 8:55am
Indicative fees current as of : 31 January 2020 4:26pm