STAT521

Computational Statistics

This paper covers maximum likelihood estimation, and the fitting of advanced regression models including non-linear models, mixture models and their generalisations. It will take a practical approach stressing the use of R packages and WinBugs or OpenBugs Bayesian software.

This paper covers maximum likelihood estimation, and the fitting of

advanced regression models including non-linear models, mixture models and their generalisations. It will take a practical approach stressing the use of R packages and WinBugs or OpenBugs Bayesian software.

Paper Information

Points: 30.0
Prerequisite(s): STAT321, or three other 300 level Statistics papers, and at the discretion of the Chairperson of Department
Internal assessment / examination: 1:0

Semesters and Locations

Occurrence Code When taught Where taught
18A (HAM)A Semester : Feb 26 - Jun 24, 2018 Hamilton

Timetabled Lectures for Computational Statistics (STAT521)

DayStartEndRoomDates
Tue4:00 PM5:00 PMG.3.33Feb 26 - Jun 3
Thu3:00 PM5:00 PMG.3.33Feb 26 - Jun 3
Fri4:00 PM5:00 PMG.3.33Feb 26 - Jun 3

NB:There may be other timetabled events for this paper such as tutorials or workshops.
Visit the online timetable for STAT521 for more details


Indicative Fees for Computational Statistics (STAT521)

Occurrence Domestic International
 Tuition Resource 
18A (HAM) $1898 $0 $7165
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

The following 2017 paper outlines are available for STAT521. Please contact the Faculty or School office for details on 2018 outlines.

Additional Information

Available Subjects:  Statistics | Data Analytics

Other available years: Computational Statistics - STAT521 (2017)

Paper details current as of : 11 January 2018 12:04pm
Indicative fees current as of : 17 January 2018 4:30am

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