At least 15 credits from Statistics A, 30 credits
The course is about linear time series models focusing on stochastic processes in discrete time. The course covers the Box-Jenkins approach to ARIMA models, that is Identification, Estimation, Evaluation and Forecasting. Fundamental concepts such as stationarity, random walks, seasonality, and Granger Causality will be covered.
