Study for the Certified Supply Chain Professional (CSCP) Practice Exam. Prepare with multiple choice questions, each accompanied by hints and explanations. Get ready to ace your exam!

Mean Absolute Deviation (MAD) is a measure used to quantify the accuracy of a forecasting method. It calculates the average of the absolute differences between actual observed values and the values predicted by the forecast. This means that for each forecast, you take the actual value, subtract the forecast value, and take the absolute value of that difference to eliminate any negative values. Then, you calculate the average of these absolute differences. This method effectively shows the average magnitude of errors in forecasted values without considering their direction (whether they are over or under the actual value).

In this context, the other options do not accurately describe MAD. The sum of forecast values does not provide insight into the accuracy of those forecasts. The median of observed values does not help in understanding deviations, as it focuses on a central value rather than the differences from forecasts. The standard deviation of forecast errors indicates how spread out those errors are but does not reflect the average absolute deviation, which is what MAD specifically measures.

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