Forecasting and Time Series

Catalog description

An introduction to creating, solving, analyzing, and interpreting real-world time-series and forecasting models. Topics include linear, autoregressive, moving average, and other forecasting and time-series techniques; transfer functions; multivariate model building; stationary and nonstationary techniques. Applications may include all areas where forecasting is required including transportation, finance, scheduling, networks, and supply chains. Appropriate software tools for analyzing forecasting models including software such as SAS and spreadsheet software will be taught. Enrollment is limited to Graduate level students.