Prerequisite(s): Consent of the Graduate Coordinator.
This course teaches students to analyze and model time series data. Students will analyze data, create forecast models, assess forecast models, and forecast future data values. This includes learning about autoregressive models, autoregressive moving average models, the ARIMA model, conditional heteroscedasticity models, vector autoregressive models, and vector error correction models. These methodologies can be used to forecast business data and data from other areas.