6 points, SCA Band 2, 0.125 EFTSL
Postgraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
- First semester 2019 (On-campus)
Students must have passed one of, , , , , or .
Forecasts are crucial for guiding the planning and decision making process in business. In this unit you will learn to apply reliable methods for generating accurate forecasts in a rapidly changing business environment. These include: an introduction to regression modelling from a forecasting perspective, classical decomposition, exponential smoothing, Box-Jenkins ARIMA modelling and judgemental forecasting. You will build your programming skills by learning to program in R, a free programming language for statistical computing.
The learning goals associated with this unit are to:
- develop statistical skills for analysing data in a business environment
- learn how to build accurate and robust models for forecasting
- acquire computer skills vital for forecasting business and economic data
- gain knowledge of the theoretical aspects of the models used.
Within semester assessment: 40% + Examination: 60%
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
See also Unit timetable information