MAPE expresses forecast errors as what?

MAPE expresses forecast errors as what?

• A. A percentage of actual values.
• B. An absolute value of errors.
• C. The squared error.
• D. A log error.

Answer: (A)

MAPE expresses forecast errors as a percentage of actual values. It takes the absolute difference between actual and forecast, divides by the actual value, multiplies by 100 to convert to a percentage, and then averages these percentages across observations. This makes errors scale-free, so you can compare accuracy across items or periods with different units or magnitudes. For example, if actual is 100 and forecast is 90, the error is |100−90|/100 = 0.10, or 10%. If actual is 50 and forecast is 60, the error is |50−60|/50 = 0.20, or 20%. By expressing errors as percentages of the actual values, MAPE provides a clear, interpretable measure of forecast accuracy.

MAPE expresses forecast errors as a percentage of actual values. It takes the absolute difference between actual and forecast, divides by the actual value, multiplies by 100 to convert to a percentage, and then averages these percentages across observations. This makes errors scale-free, so you can compare accuracy across items or periods with different units or magnitudes. For example, if actual is 100 and forecast is 90, the error is |100−90|/100 = 0.10, or 10%. If actual is 50 and forecast is 60, the error is |50−60|/50 = 0.20, or 20%. By expressing errors as percentages of the actual values, MAPE provides a clear, interpretable measure of forecast accuracy.