Computational Bayesian Statistics - STATS326 (2019)

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
19B (HAM)B Semester : 8 Jul 2019 - 3 Nov 2019 Hamilton

Timetabled Lectures for Computational Bayesian Statistics (STATS326)

DayStartEndRoomDates
Tue2:00 PM4:00 PMG.3.33Jul 8 - Oct 13
Thu3:00 PM4:00 PMG.3.33Jul 8 - Oct 13

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)

Occurrence Domestic International
 Tuition Resource 
19B (HAM) $765 $0 $3053
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.

Paper Outlines

Paper outlines are currently not available for this paper. Please contact the Faculty or School office for further details.

Additional Information

Available Subjects:  Data Analytics | Statistics

Paper details current as of : 18 February 2019 3:37pm
Indicative fees current as of : 5 February 2019 5:10pm

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