Examples of time series. Time series plot. Model-building strategy. Classical trend and seasonal model. Additive and multiplicative models. Decomposition. Exponential smoothing. Estimation. Forecasting using Holt-Winters method. Time series and stochastic processes. Autocovariance function. Random walk. Moving Average. White Noise. Stationarity. Models for stationary time series : general linear process, MA processes. AR processes. Invertibility. Box-Jenkins methods. ARIMA and SARIMA processes. Models for non-stationary time series. Differencing. Model specification. Properties of sample acf and pacf. Nonstationarity. AIC criterion. Model Estimation and diagnostics. Residual analysis. Box-Pierce and Ljung-Box statistics. Forecasting. Using R Statistical Language for time series analysis.