Percent Error Calculator
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What Your Result Means
- Percent Error: How far your experimental measurement is from the theoretical (accepted) value, expressed as a percentage. Lower is better — under 5% is generally considered good for most lab work.
- Absolute Error: The raw numerical difference between the two values, without the percentage conversion. Useful when you need to report error in the same units as the measurement.
- Sign Doesn't Matter: This calculator uses the absolute value of the difference, so it always returns a positive percent error regardless of whether the experimental value is above or below the theoretical.
How This Calculator Works
You enter an experimental (measured) value and a theoretical (accepted) value. The tool computes the absolute error as |experimental − theoretical|, then divides by the absolute value of the theoretical and multiplies by 100 to get the percent error. If the theoretical value is zero, percent error is undefined because you cannot divide by zero. The calculator does not perform error propagation or account for systematic vs. random error.
Quick Questions
What's a "good" percent error?
It depends on the field and experiment. In introductory chemistry or physics labs, under 5% is typically considered good. Precision instruments may require errors below 1%. The acceptable range depends on your measurement tools and the sensitivity of the experiment.
What if my theoretical value is zero?
Percent error is undefined when the theoretical value is zero because the formula requires dividing by it. In that case, report the absolute error instead, or use a different error metric like relative difference.
Is percent error the same as percent difference?
No. Percent error compares a measured value to an accepted/known value. Percent difference compares two measured values to each other, dividing by their average. Use percent error when you have a known reference value.
Should I use the signed or unsigned version?
The unsigned (absolute) version is standard for reporting accuracy. The signed version can be useful to show whether your measurement is consistently too high (positive) or too low (negative), which may indicate systematic bias.
Sources
- NIST — Measurement Uncertainty (measurement standards and error reporting)
- Wikipedia — Approximation Error (percent error formula and variants)
Method & review
Estimate only. Results reflect your inputs and standard formulas. Double-check important decisions independently.