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Percentage Error Calculator

Calculate percentage error between measured and true values

Results are estimates for informational purposes only — not professional financial, medical, or legal advice. See how we build and verify our calculators.

Frequently Asked Questions

What is percentage error?

Percentage error = |experimental - actual| / |actual| x 100%. It measures how far off a measured value is from the true value. A 2% error means your measurement was 2% away from the true value. Lower percentage error = more accurate measurement.

Why use absolute value in percentage error?

The absolute value |experimental - actual| gives us the magnitude of the error regardless of direction. Without it, being 5% too high and 5% too low would cancel out. Percentage error is always reported as a positive number representing the size of the discrepancy.

What percentage error is acceptable in science?

Depends on the field: Physics lab (student level): <5% is good, <10% acceptable. Analytical chemistry: <2%. Manufacturing quality control: often <1%. Medical devices: <0.5% or even less. Research science: depends on the measurement, but typically strive for <5%.

What is the difference between percent error and percent difference?

Percent error compares a measurement to a known true value: |measured - true| / |true| x 100%. Percent difference compares two measurements neither of which is designated the true value: |A - B| / ((A+B)/2) x 100%. Use percent error when a true value is known; percent difference when comparing two measurements.

How do I reduce experimental error?

Systematic errors (shift in one direction): calibrate equipment, use better measuring tools, control experimental conditions. Random errors (scatter in both directions): repeat measurements and average, use larger sample sizes. Human errors: double-check readings, use digital instruments, blind measurements.

Acceptable Error by Field

FieldTypical Acceptable Error
Student physics lab< 10%
Engineering< 5%
Analytical chemistry< 2%
Medical devices< 1%
Precision manufacturing< 0.5%
Research science< 5% typical

Error Types

Systematic Error
Consistent bias in one direction. Caused by faulty calibration, instrument zero offset. Cannot be reduced by averaging.
Random Error
Unpredictable scatter in both directions. Reduced by taking more measurements and averaging results.
Human Error
Reading scales wrong, parallax, transcription errors. Reduced by careful technique and digital instruments.