ETC5580 Advanced statistical modelling
Faculty of Business and Economics
ETC5580 Advanced statistical modelling is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2025 in Semester 1 at Clayton. It needs ETW2510, ETC5242, ETC2410, ETF2100, ETC5256, ETF5910, ETC2420 or ETC3440 and unlocks 2 units.
- Credit points
- 6
- Offered in 2025
- Semester 1
- Clayton
- Assessment
- Exam 60%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2025 handbook entry. See the 2027 entry.
Reviews
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Requisites
Before ETC5580
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
- ETW2510Introduction to econometricsNo reviews yet
- ETC5242Statistical thinkingNo reviews yet
- ETC2410Introductory econometricsNo reviews yet
- ETF2100Introductory econometricsNo reviews yet
- ETC5256Statistical modelling for actuarial studiesNo reviews yet
- ETF5910Introductory applied econometricsNo reviews yet
- ETC2420Statistical thinkingNo reviews yet
- ETC3440Introductory econometricsNo reviews yet
After ETC5580
2 units list ETC5580 as a prerequisite or corequisite.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit introduces extensions of linear regression models for handling a wide variety of data analysis problems. Three extensions will be considered: generalised linear models for handling counts and binary data; mixed-effect models for handling data with a grouped or hierarchical structure; and non-parametric regression for handling non-linear relationships. All computing will be conducted using R.
Offerings in 2025
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | Blended |
Assessment
- Within semester assessment40%
- Examination60%
Learning outcomes
When you finish this unit, you should be able to:
- 1
provide an understanding of statistical models for handling common data analysis problems
- 2
develop skills for fitting, interpreting and assessing statistical models
- 3
develop computer skills for exploring and modelling different kinds of data.
Workload and teaching
- Workshops12 hours
- Tutorials12 hours
- Seminars24 hours
- Teaching approachProblem-based learning
- Teaching approachActive learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.
This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.
This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
Learning resources
Technology resources
There may be an additional cost associated with purchasing a physical and/or virtual calculator. Specific details will be provided in the Learning Management System by commencement of Orientation week.
Contacts
- Chief Examiners
- Dr Didier Nibbering
Common questions
What are the prerequisites for ETC5580?
You need ETW2510, ETC5242, ETC2410, ETF2100, ETC5256, ETF5910, ETC2420 or ETC3440 before you enrol.
What can I take after ETC5580?
ETC5580 is a prerequisite or corequisite for 2 units, including ETC4500 and ETC5450.
When is ETC5580 offered?
In 2025, ETC5580 runs in Semester 1 at Clayton.
How much work is ETC5580?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETC5580 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 1 other task.