Time series analysis is a statistical technique used to analyze sequential or chronological data points collected over a period of time. It involves studying the patterns, trends, and correlations within the data to make predictions or forecasts about future behavior. This type of analysis is commonly used in various fields such as economics, finance, weather forecasting, and signal processing. Time series analysis techniques include autocorrelation, trend analysis, seasonal decomposition, and forecasting models like ARIMA and exponential smoothing.