Time Series and Forecasting

What it covers

This course provides you with a working knowledge of forecasting methods. Techniques in univariate forecasting using exponential smoothing, regression methods for time series data, stationary and non-stationary time series models for seasonal and non-seasonal time series data and model selection procedures are covered. The emphasis is on methods and the analysis of time series data using the R statistical software. Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. (This applies to students who commence enrolment in a bachelor or honours program from 1 January 2016 onwards. See the WAM information web page for more information.)

Assessment

Assessment not published yet.

When and where