Predictive Analytics (QBUS2820)


Predictive analytics are a set of tools to enable managers to exploit the patterns found in transactional and historical data. For example major retailers will invest in predictive analytics to understand, not just consumers' decisions and preferences, but also their personal habits, so as to more efficiently market to them. This unit introduces different techniques of data analysis and modelling that can be applied to traditional and non-traditional problems in a wide range of areas including stock forecasting, fund analysis, asset allocation, equity and fixed income option pricing, consumer products, as well as consumer behaviour modelling (credit, fraud, marketing). The forecasting techniques covered in this unit are useful for preparing individual business forecasts and long-range plans. The unit has a practical approach with many up-to-date datasets used for demonstration in class and in the assignments.

Our courses that offer this unit of study

Further unit of study information


1x 2hr lecture and 1x 1hr tutorial per week


assignment 1 (20%), assignment 2 (30%), mid-term exam (20%), final exam (30%)

Faculty/department permission required?


Unit of study rules


QBUS2810 or ECMT2110

Study this unit outside a degree

Non-award/non-degree study

If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student.

Cross-institutional study

If you are from another Australian tertiary institution you may be permitted to underake cross-institutional study in one or more units of study at the University of Sydney.