ARMA stands for AutoRegressive Moving Average, a statistical model 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 when data shows patterns over time, such as trends or seasonality. By capturing these patterns, ARMA helps in making informed decisions in various fields, including finance, economics, and environmental studies, where understanding time-dependent data is crucial.