Forecast Error MAE and RMSE Calculator
Evaluate paired actual and forecast values with signed bias, absolute errors and explicitly defined percentage metrics.
YOUR CALCULATION
Result
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Calculation steps
Work through one step at a time or reveal the complete calculation. The steps use your current inputs.
How to calculate
Define error as forecast minus actual. Average absolute errors for MAE and squared errors for MSE, then take its square root for RMSE. Report percentage metrics with their zero rules.
MAE=mean(|forecast−actual|); RMSE=sqrt(mean(error²)); bias=mean(forecast−actual)
Worked example
For actuals 100,120,80 and forecasts 110,115,75, errors are +10,−5,−5. MAE is 6.6667, RMSE 7.0711 and bias zero.
Assumptions and input details
1–200 paired observations; every row is equally weighted. MAPE omits actual=0 and reports the included count; WAPE divides total absolute error by total absolute actual value, and is undefined when that denominator is zero. sMAPE uses 200|F−A|/(|A|+|F|), with a both-zero pair contributing zero. Percentage errors can be unstable near zero. These are entered-sample scores, not cross-validation or future accuracy guarantees.
Using this calculator
Can I enter my own problem?
Yes. Replace the example values with your own inputs. The result, calculation steps, tables and applicable diagrams update from those inputs. Blank or invalid values clear the result; example values are never silently substituted for missing inputs.
Are the results exact?
Results use floating-point arithmetic and displayed rounding. Read the formula, assumptions and any stated data precision before interpreting the result.
Is my input uploaded?
The calculation runs in your browser. No account, file upload or external AI service is required. Inputs are not saved between page reloads.
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