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.
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