The measure of forecast error where the absolute amount of error of each forecast is averaged is
A) mean squared error (MSE).
B) mean absolute deviation (MAD).
C) mean absolute percentage error (MAPE).
D) bias.
E) the tracking signal.

Question

Quizplus · Accepted Answer

The measure described in the question is the definition of mean absolute deviation (MAD). Therefore, B is the correct choice. Mean squared error (A) equals the average of the squared errors, while mean absolute percentage error (C) calculates the error as a percentage of the actual value. Bias (D) measures the systematic difference between actual values and their forecasted values. Tracking signal (E) is used to monitor forecast performance over time and is calculated by dividing the cumulative error by the mean absolute deviation. However, none of these measures match the description given in the question. Thus, only B is the best choice.

The Measure of Forecast Error Where the Absolute Amount of Error