STAT 131: An introduction to time series models and associated methods of data analysis and inference. Auto regressive (AR), moving average (MA), ARMA, and ARIMA processes, stationary and non-stationary processes, seasonal processes, auto-correlation and partial auto-correlation functions, identification of models, estimation of parameters, diagnostic checking of fitted models, forecasting, time domain regression approach including Box-Jenkins method, and spectral analysis.

STAT 231: Meets with STAT 131 but graduate students will be exposed to more rigorous treatment of time series analysis.