Advanced Topics in Predictive Analytics

Catalog description

In this advanced course in predictive analytics, students learn the basic theory of stationary processes, linear filters, spectral analysis, ARIMA models, forecasting and smoothing, models for trends and seasonal patterns, and autoregression and time series regression models. Hierarchically introduced methods start with terminology and exploratory graphics, moving to descriptive statistics, and ending with modeling, forecasting procedures and practical applications. Emphasis is on the practical application of time series models.