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:	100:0
Restriction(s):	STAT326

Trimesters and Locations

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

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Timetabled Lectures for Computational Bayesian Statistics (STATS326)

Day	Start	End	Room	Dates
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)

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.
Occurrence	Domestic		International
	Tuition	Resource
20B (HAM)	$780		$3145

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.