units

ETC2450

Faculty of Business and Economics

print version

6 points, SCA Band 3, 0.125 EFTSL

Undergraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Business and Economics

Organisational Unit

Department of Econometrics and Business Statistics

Coordinator(s)

Professor Rob Hyndman

Offered

Not offered in 2017

Synopsis

Reliable forecasts of business and economic variables must often be obtained against a backdrop of structural change in markets and the economy. This unit provides a practical introduction to methods suitable for forecasting in these circumstances including the classical decomposition of time series, exponential smoothing, Box-Jenkins ARIMA modelling, and regression with auto-correlated disturbances. It also provides an introduction to applied multiple regression analysis. Students can expect to enhance their computer skills with exercises using advanced features of Microsoft Excel and an econometrics package.

Outcomes

The learning goals associated with this unit are to:

  1. provide an understanding of common statistical methods used in business and economic forecasting
  2. develop computer skills for forecasting from business and economics time series data
  3. provide insights into the problems of implementing and operating large scale forecasting systems for use in production and services management.

Assessment

Within semester assessment: 40%
Examination: 60%

Workload requirements

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

Chief examiner(s)

Professor Rob Hyndman

Prerequisites