ARIMA (short for AutoRegressive Integrated Moving Average) is a classic statistical model for time series forecasting. It works by combining three elements: autoregression (using past values to predict future ones), integration (removing trends to make data stationary), and moving averages (capturing patterns in forecast errors). For analysts, it’s valuable because it turns historical data into … Continue reading Copilot in Excel: How to build ARIMA forecasts with Python