The AutoRegressive Moving Average (ARMA) model is a statistical tool used for analyzing and forecasting time series data. It combines two components: the AutoRegressive (AR) part, which uses past values of the series to predict future values, and the Moving Average (MA) part, which uses past forecast errors to improve predictions. This model is particularly useful for data that shows patterns over time. ARMA models are commonly applied in various fields, including economics, finance, and environmental science, to understand trends and make informed decisions. By capturing both the autoregressive and moving average aspects, ARMA provides a comprehensive approach to modeling time-dependent data, making it a valuable resource for analysts and researchers.