The **mean absolute percentage error **(MAPE) is a measure of how accurate a forecast system is. It measures this accuracy as a percentage, and can be calculated as the average absolute percent error for each time period minus actual values divided by actual values.

## Formula for Mean Absolute Percentage Error

- n is the number of fitted points,
- A
_{t}is the actual value, - F
_{t}is the forecast value. - Σ is summation notation (the absolute value is summed for every forecasted point in time).

The mean absolute percentage error (MAPE) is the most common measure used to forecast error, and works best if there are no extremes to the data (and no zeros).

## References

Beyer, W. H. CRC Standard Mathematical Tables, 31st ed. Boca Raton, FL: CRC Press, pp. 536 and 571, 2002.

Agresti A. (1990) Categorical Data Analysis. John Wiley and Sons, New York.

Dodge, Y. (2008). The Concise Encyclopedia of Statistics. Springer.

Everitt, B. S.; Skrondal, A. (2010), The Cambridge Dictionary of Statistics, Cambridge University Press.

**CITE THIS AS:**

**Stephanie Glen**. "Mean Absolute Percentage Error (MAPE)" From

**StatisticsHowTo.com**: Elementary Statistics for the rest of us! https://www.statisticshowto.com/mean-absolute-percentage-error-mape/

**Need help with a homework or test question? **With **Chegg Study**, you can get step-by-step solutions to your questions from an expert in the field. Your first 30 minutes with a Chegg tutor is free!

**Comments? Need to post a correction?** Please post a comment on our ** Facebook page**.