This lecture provides an introduction to time series analysis, focusing on concepts such as stationarity, autocorrelation, and transformations like log returns to achieve stationarity in financial data. It also covers key models including autoregressive (AR), moving average (MA), and combined ARMA models, explaining their properties, estimation methods, and how differencing can handle non-stationary series.