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The course aims to teach forecasting techniques for manufacturing and service operations. The techniques include time series decomposition, regression methods, smoothing techniques, regression methods, exponential smoothing and Box-Jenkins ARIMA models. Ultimate goal is to teach techniques for comparing individual methodologies, selecting a methodology and designing a forecasting system for a given organization.
Statistical forecasting methods. Time series decomposition. Regression. Exponential smoothing. Box-Jenkins ARIMA models.
Upon succesful completion of this course, a student will be able to
1. Apply basic techniques of data analysis and forecasting [a2] [B3]
2. Distinguish between short-term andlong-term forecasting (B4, a2)
3. Compare individual forecasting methodologies(B6, c)
4. Choose and defend the most appropriate forecasting methodin different situations. (B6, c)
5. Designa forecasting system for a given organization(B5, c)
6. Evaluate the performance of forecasting methods (B6, b2,h)