Time Series Analysis is a method of analyzing time series data to extract meaningful statistics and other characteristics of the data. Time series data consists of sequences of observations recorded at regular time intervals. Techniques in time series analysis include decomposition, autocorrelation, and forecasting models such as ARIMA (AutoRegressive Integrated Moving Average) and exponential smoothing. Time series analysis is used in a variety of fields, including finance, economics, meteorology, and engineering, to understand trends, seasonal patterns, and cyclic behavior, and to make predictions about future values.