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STAT 4603 [0.5 credit] Time Series and Forecasting (Honours)

Time series regression. Nonstationary and stationary time series models. Nonseasonal and seasonal time series models. ARIMA (Box-Jenkins) models. Smoothing methods. Parameter estimation, model identification, diagnostic checking. Forecasting techniques. A statistical software package will be used.
Includes: Experiential Learning Activity
Prerequisite(s): STAT 3553 or STAT 3503, or permission of the School.
Lectures three hours a week.