About
Introduces techniques for analyzing data collected at different points in time. Emphasizes probability models, forecasting methods, analysis in both time and frequency domains, linear systems, state-space models, intervention analysis, transfer function models and the Kalman filter. Explores stationary processes, autocorrelations, and autoregressive, moving average, and ARMA processes, among other topics.