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Unit of study_
QBUS3840: Choice Modelling
2025 unit information
How do business analysts model firm or consumer behaviour quantitatively How do analysts model brand choice in marketing or travel mode choice in transport These questions are answered by modelling choices with statistical tools designed for qualitative or discrete data such as logistic regressions rather than the standard linear regression models This unit investigates various quantitative modelling techniques relevant for choice modelling through business cases in marketing transport research strategy economics and other relevant business fields This unit also explores models that pool observations on a crosssection of households countries firms etc over several time periods This is known as panel data models which are increasingly relevant in all areas of Business with the growing availability of new sources of data
Unit details and rules
Managing faculty or University school:
Business (Business School)
| Study level | Undergraduate |
|---|---|
| Academic unit | Business Analytics |
| Credit points | 6 |
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Prerequisites:
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QBUS2810 or DATA2002 or ECMT2110 |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. predict consumer behaviour based on mathematical models derived from experimental data
- LO2. interpret, explain and criticise the results of model-based analysis of consumer choice.
- LO3. design experiments and curate existing data to capture consumer behaviour in a cost-efficient manner.
- LO4. use and extend data analysis software tools for modelling choice.
- LO5. incorporate modern machine learning techniques to choice analysis and prediction.
Unit availability
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The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 2 2025
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Normal day | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
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