ETX3231 - Business forecasting - 2018

Basic forecasting tools. Review of basic time series analysis techniques. Moving averages and exponential smoothing forecasting methods. Box-Jenkins method of forecasting. Comparison of forecasting techniques. Introduction to time series regression and dynamic models. Applications to time series from the accounting, economics, banking, finance and management areas. Excel and SPSS will be used.

The learning goals associated with this unit are to:

1. identify the basic tools of forecasting and define the basic time series analysis techniques
2. describe the decomposition techniques, exponential smoothing forecasting techniques and Box-Jenkins method of forecasting
3. compare the forecasts of real economic, business and financial time series by decomposition techniques and exponential smoothing techniques using Excel and Box Jenkins method using SPSS
4. differentiate between decomposition methods, exponential smoothing methods and autoregressive methods of forecasting
5. analyse time series in the business environment using the appropriate methods and interpret computer output.

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