Which statement accurately summarizes the interpretation of Mean Absolute Deviation $($MAD$)$ and Mean Squared Error $($MSE$)$ in forecasting?

Group of answer choices

MAD focuses on minimizing large errors, while MSE prioritizes minimizing small errors.

MAD highlights significant forecasting errors, while MSE operates as a meticulous accountant, diligently correcting minor discrepancies in the data.

A lower MAD$/$MSE indicates a better forecasting accuracy.

A higher MAD$/$MSE suggests a stronger fit of the forecasting model to the data.