What are the Mean Absolute Deviation (MAD) and the Mean Squared Error (MSE) for the current…

➤ Why do MAD and MSE matter when evaluating forecasts?
MAD gives a simple, interpretable measure of typical forecast error. MSE emphasizes variability and penalizes large deviations, which helps detect inconsistency or extreme misses. Together they guide model selection, tuning, and operational decisions, and they relate to RMSE and loss functions used in statistical estimation and forecasting performance assessment.