Time series forecasting: Principles and practice

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.

Problem-based learning - This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.

Active learning - This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.

Enquiry-based learning - This unit engages you in enquiry-based learning, where you will be encouraged to use your own knowledge to develop and engage in a process of enquiry, study and research to identify areas to be investigated and an approach to doing so.

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.