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Uncertainty Calculator

Calculate measurement uncertainty and confidence intervals

Calculate Uncertainty

How to Use

  1. Enter your measured value
  2. Enter the standard deviation of your measurements
  3. Enter the number of measurements taken
  4. Select the desired confidence level
  5. Click calculate to see uncertainty analysis

What is Measurement Uncertainty?

Measurement uncertainty quantifies the doubt about a measurement result. It represents a range within which the true value is expected to lie with a specified probability.

Uncertainty is essential in science and engineering for assessing data quality, comparing measurements, and making informed decisions based on experimental results.

Confidence Intervals

A confidence interval is a range of values that likely contains the true value. Common confidence levels:

  • 68% confidence (±1σ): About 2/3 of measurements fall within this range
  • 95% confidence (±2σ): Standard for most scientific work
  • 99% confidence (±3σ): Used for critical applications requiring high certainty

Reducing Measurement Uncertainty

  • Increase the number of measurements (n)
  • Use more precise measuring instruments
  • Control environmental conditions
  • Calibrate instruments regularly
  • Train operators to reduce human error
  • Use proper measurement techniques

Frequently Asked Questions

What is the difference between standard deviation and standard error?
Standard deviation measures the spread of individual measurements, while standard error measures the precision of the mean. Standard error decreases as you take more measurements: SE = σ/√n.
Why should I use confidence intervals?
Confidence intervals provide a range that likely contains the true value, accounting for measurement variability. They're more informative than point estimates alone and essential for scientific reporting.
How many measurements do I need?
More measurements reduce uncertainty and improve precision. For rough estimates, 10-30 measurements are typical. For critical work, 50+ measurements may be needed. The law of diminishing returns applies as n increases.
When should I report absolute vs relative uncertainty?
Report absolute uncertainty (±value) when the magnitude matters. Use relative uncertainty (percentage) when comparing measurements of different scales or when proportional error is more meaningful.

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