Predictive Analytics (MGMT90216)
Graduate courseworkPoints: 6.25Not available in 2025
About this subject
Overview
| Fees | Look up fees |
|---|
Predicting key business and economic variables is increasingly important, as it drives both objective decision-making and improved profitability. This course aims to cover the basic forecasting methods used to predict business and economic variables, based on historical data. These include traditional regression, time series, as well as emerging methods such as ensemble forecasts. Throughout, the focus will be on practical implementation of forecasting techniques using the publicly available software “R”. The importance of benchmarking, the assessment of forecasts from different models, and the use of forecasts in decision-making frameworks, will also be highlighted.
Intended learning outcomes
On completion of this subject, students should be able to demonstrate;
- an understanding of a range of models relevant to forecasting time series data.
- the skills to apply appropriate modelling and forecasting techniques in the “R” software to business and economic contexts, and to critique and compare competing methodologies.
- the skills to translate forecasting outputs to information and provide recommendation for relevant business problems.
Last updated: 4 March 2025
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| MGMT90215 | Introduction to Data Analytics | Not available in 2025 |
6.25 |
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 |
|---|---|---|
Multiple-choice on the different predictive methods covered in the subject
| To be completed on the end of the second day | 20% |
Essay – develop a recommendation for operationalizing predictive methods in a business case, and how they can be used to improve decision-making
| 4 Weeks after the end of teaching | 80% |
Last updated: 4 March 2025
Dates & times
Not available in 2025
Additional delivery details
This subject is a quota subject and places are limited. Students may provisionally enrol via the Student Portal, but places are not guaranteed until selection is completed. You will be notified in writing by the Student Centre if you are selected.
The students will be selected on the first come, first served basis. If any student is approaching the course completion date, s/he will get priority in enrolment.
Last updated: 4 March 2025
Further information
- Texts
Last updated: 4 March 2025