Predictive Business Analytics (BUSA90541)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
Availability | May |
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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