The measure of forecast error where the amount of error of each forecast is squared and then an average is calculated is
A)mean squared error (MSE).
B)mean absolute deviation (MAD).
C)mean absolute percentage error (MAPE).
D)the tracking signal.

Question

Quizplus · Accepted Answer

The measure described in the question is the mean squared error (MSE). It is commonly used in forecasting to measure the accuracy of a model's forecasts. Squaring each error ensures that both positive and negative errors are weighted equally, and taking the average of these squared errors provides a simple measure of the overall magnitude of forecasting errors.

The Measure of Forecast Error Where the Amount of Error