Mean Absolute Percentage Error Calculator
MAPE expresses absolute forecast errors relative to each observed value, making the result a percentage.
How to use this calculator
- Enter matching observed and predicted lists separated by semicolons; do not include zero observed values.
- Check that every input uses the stated units and covers the same period, population or project scope.
- Change one assumption at a time when comparing scenarios.
Formula used by mean absolute percentage error calculator
MAPE = mean(|observed − predicted| ÷ |observed|) × 100
- MAPE = mean(|observed − predicted| ÷ |observed|) × 100
- Observed values must be non-zero. MAPE can behave poorly near zero and may favour particular forecast patterns.
- Inputs are validated against the tool-specific constraints; displayed results are rounded for readability.
Worked examples
Worked example
Compare observed values 100; 120; 80; 150 with predictions 95; 125; 84; 144 to obtain a mean percentage error measure.
The calculator averages absolute percentage errors for matching observations.
The calculator averages absolute percentage errors for matching observations.
Understanding the result
MAPE expresses absolute forecast errors relative to each observed value, making the result a percentage.
Observed values must be non-zero. MAPE can behave poorly near zero and may favour particular forecast patterns.
Important notes
Observed values must be non-zero. MAPE can behave poorly near zero and may favour particular forecast patterns.
Treat the result as an estimate for the assumptions entered; verify important specifications against the relevant source or professional guidance.
Frequently asked questions
Why must observed values be non-zero?
Each percentage error divides by its observed value, so zero makes the metric undefined.
Can MAPE compare every forecast?
Use caution with zeros, near-zero values, negative observations and data sets with different characteristics.
How should I use this result?
Enter matching observed and predicted lists separated by semicolons; do not include zero observed values.
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- Standard Error Calculator — Estimate the standard error of a sample mean from sample standard deviation and sample size.
- Confidence Interval for Mean Calculator — Estimate a normal-approximation confidence interval around a sample mean from its spread and sample size.
Related explanations
Learn the method behind the number or compare the terminology before using the calculator.
- How to Calculate a Z-Score — Learn how a z-score shows how far a value is from the mean in standard-deviation units.
- How to Calculate Percentage Change — Learn the percentage change formula, how to calculate increases and decreases, and why the original value matters.
- Percent Difference — Understand percent difference, when it is appropriate, and how it differs from percentage change and percent error.
This page provides a calculation tool plus explanatory information so you can understand what the result means and when the underlying method may not fit your situation.