• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Classification Transitional
  • Course subject Statistics
  • Areas of interest Statistics
  • Academic career PGRD
  • Course convener
    • Dr Luca Maestrini
    • Dr Tao Zou
  • Mode of delivery In Person
  • Co-taught Course
  • Offered in Summer Session 2023
    Second Semester 2023
    See Future Offerings

This course is intended to introduce students to generalised linear modelling methods, with emphasis on, but not limited to, common methods for analysing categorical data. Topics covered include a review of multiple linear regression and the analysis of variance, log-linear models for contingency tables, logistic regression for binary response data, Poisson regression, model selection and model checking , mixed effects models. Additional topics may include Bayesian analysis for generalized linear models and generalized mixed effect models.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Explain in detail the role of generalised linear modelling techniques (GLMs) in modern applied statistics and implement methodology.
  2. Demonstrate an in-depth understanding of the underlying assumptions for GLMs and perform diagnostic checks whilst identifying potential problems.
  3. Perform statistical analyses using statistical software, incorporating underlying theory and methodologies.

Other Information

Offerings of this course outside of Semester 1 and Semester 2 are available only to students enrolled in MADA.

Indicative Assessment

  1. The research-based assessment will consist of assignments. (50) [LO 1,2,3]
  2. The other assessment may include but is not restricted to: exams, quizzes, presentations and other assessments as appropriate. (50) [LO 1,2,3]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have completed STAT6038 or STAT6014 or STAT7001. Incompatible with STAT3015 and STAT4030.

Prescribed Texts

Information about the prescribed textbook will be available via the Class Summary.

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
1
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2023 $4320
International fee paying students
Year Fee
2023 $6180
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Summer Session

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
1604 01 Jan 2023 20 Jan 2023 20 Jan 2023 31 Mar 2023 In Person View

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
7279 24 Jul 2023 31 Jul 2023 31 Aug 2023 27 Oct 2023 In Person View

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