Predictive Business Analytics (BUSA90541)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | May |
|---|---|
| Fees | Look up fees |
Predicting key business and economic variables is increasingly important, as it drives both objective decision-making and improved profitability. This component aims to cover the main methods used to predict business and economic variables, based on historical data. These include traditional regression, time series, multivariate and econometric models, as well as emerging methods such as ensemble forecasts. Both point and density prediction will be considered, along with metrics for the quality of both. Throughout, the focus will be on introducing methods in the context of substantive business and economic problems, using a wide range of prediction methods. The importance of benchmarking different methodologies, and the use of prediction in decision-making frameworks, will also be stressed.
Intended learning outcomes
On completion of this subject, students should be able to:
- Understand a wide range of models and methodologies relevant to predicting business outcomes.
- Apply appropriate modelling and forecasting techniques to business and economic contexts, and to critique and compare competing methodologies.
- Translate forecasting outputs to information and provide recommendations to address the relevant business problems.
Last updated: 4 March 2025
Eligibility and requirements
Prerequisites
Pre-requisite
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| BUSA90536 | Statistical Learning for Business | March (On Campus - Parkville) |
12.5 |
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 4 March 2025
Assessment
| Description | Timing | Percentage |
|---|---|---|
Individual assignment
| Week 3 | 20% |
Syndicate assignment
| Week 6 | 30% |
Final examination
| Week 9 | 50% |
Last updated: 4 March 2025
Dates & times
- May
Mode of delivery On Campus (Parkville) Contact hours 24 hours lecturing and 24 hours of tutorials Total time commitment 170 hours Teaching period 26 May 2025 to 18 July 2025 Last self-enrol date 5 June 2025 Census date 13 June 2025 Last date to withdraw without fail 4 July 2025 Assessment period ends 25 July 2025
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 4 March 2025
Further information
- Texts
Last updated: 4 March 2025