ETW3420 · Time series forecasting: Principles and practice

Overview

Obtaining reliable forecasts of business and economic variables is a challenging task that organisations face. With a focus on time series data, you will be introduced to forecasting methods commonly used in practice. These methods include the decomposition of time series, exponential smoothing, and ARIMA modelling. You can expect to enhance your computer skills with exercises using R.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. develop business research reports to communicate insights/implications derived from forecasts
2. produce forecasting models from business and economic time series data
3. apply and analyse appropriate statistical methods for business and economic forecasting
4. demonstrate computer skills for predicting various business scenarios in forecasting.

Workload

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. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.