4825. Applied Time Series
3.00 credits
Prerequisites:
Grading Basis: Graded
Introduction to prediction using time-series regression methods with non-seasonal and seasonal data. Smoothing methods for forecasting. Modeling and forecasting using univariate, autoregressive, moving average models.
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