In forecasting, MAE and MAPE stand for what?

• A. MAE is mean absolute error; MAPE is mean absolute percentage error
• B. MAE is median absolute error; MAPE is mean absolute percentage error
• C. MAE is mean absolute error; MAPE is maximum absolute percentage error
• D. MAE is mean actual error; MAPE is mean adjusted percentage error

Answer: (A)

Mean absolute error and mean absolute percentage error are standard forecast accuracy metrics. MAE measures forecast accuracy by averaging the absolute differences between forecasted and actual values, so it’s in the same units as the thing you’re forecasting. MAPE takes those absolute differences and expresses them as a percentage of the actual values, giving a normalized sense of error that’s easy to compare across different series.

This option correctly names both terms: MAE as mean absolute error and MAPE as mean absolute percentage error. The other choices mix up definitions—median vs mean, or label MAE as an actual error, or call MAPE a maximum or adjusted percentage error. For example, with actuals 100, 120, 80 and forecasts 110, 115, 90, MAE would be the average of |10|, |5|, | -10|, while MAPE would be the average of those absolute errors divided by the actual values, shown as a percentage.