Time series analysis is a statistical technique used to analyze and interpret data that is collected and measured over time. It involves identifying patterns, trends, and relationships within the data to make predictions and forecasts. Time series analysis is commonly used in a wide range of fields such as economics, finance, meteorology, and engineering to understand and analyze time-dependent data. Methods used in time series analysis include autoregressive integrated moving average (ARIMA) modeling, exponential smoothing, and spectral analysis.