Percent Error Calculator
Calculate percent error between theoretical and experimental values
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📚 Examples, Rules & Help
⚡Quick Examples - Try These Calculations
🔍How It Works
Error Types
Absolute Error: |Experimental - Theoretical|
Relative Error: Absolute Error ÷ |Theoretical|
Percent Error: Relative Error × 100%
Example: Theoretical = 10, Experimental = 9.5
Absolute Error = |9.5 - 10| = 0.5
Percent Error = (0.5 ÷ 10) × 100% = 5%
Sources of Error
Systematic Errors: Consistent bias in measurements
Random Errors: Unpredictable variations
Human Errors: Mistakes in reading or recording
Reducing Error:
• Calibrate instruments regularly
• Take multiple measurements
• Use appropriate precision tools
Accuracy vs Precision
Accuracy: How close to the true value
Precision: How consistent measurements are
Ideal scenario: High accuracy + High precision
Common issue: High precision but low accuracy (systematic error)
🌍Real-World Applications
❓Frequently Asked Questions
What's the difference between percent error and percent difference?
Percent Error: Compares experimental to a known theoretical value
Percent Difference: Compares two experimental values with no true reference
Use percent error when you have a known correct value to compare against.
Can percent error be negative?
No, percent error is always positive because we use absolute value.
This focuses on the magnitude of error, not the direction.
If direction matters, calculate the raw error: (Experimental - Theoretical) ÷ Theoretical × 100%
What's considered acceptable percent error?
Excellent: < 1% (high precision instruments)
Good: 1-5% (most laboratory work)
Acceptable: 5-10% (educational experiments)
Poor: > 10% (indicates measurement problems)
What if the theoretical value is zero?
Percent error is undefined when the theoretical value is zero.
In this case, use absolute error or a different error metric.
Consider whether zero is truly the expected value or if there's a measurement issue.
🎯Common Use Cases
🔬 Laboratory Analysis
- • Chemical concentration analysis
- • Physical constant measurements
- • Instrument calibration checks
- • Quality assurance testing
🎓 Educational Settings
- • Student lab report evaluation
- • Experiment accuracy assessment
- • Measurement skill development
- • Data analysis exercises
🏭 Industrial Applications
- • Product specification compliance
- • Process optimization
- • Equipment performance monitoring
- • Batch quality verification
📊 Research & Development
- • Theoretical model validation
- • Prototype performance testing
- • Simulation accuracy assessment
- • Experimental design evaluation