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The course is concerned with the theory and application of appropriate statistical techniques for analysis of time series data -- data collected over time. The course will develop a sound understanding of the time domain properties and common models for stationary and non-stationary time series in discrete time. The topics include the theory of stationary time series; methods for trend and seasonal analysis and adjustment; modelling and forecasting with autoregressive moving avarage processes; modelling the impact of exogenous or intervention variables on responses; models for stochastic volatility and long term dependence; regression models for time series counts. Applications are primarily drawn from finance and public health. SAS is used to perform appropriate analyses.

Study Level


Offering Terms

Term 2



Delivery Mode

Fully on-site

Indicative contact hours


Course Outline

To access course outline, please visit:


Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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