Error Propagation Calculator

Combine measurement uncertainties through a calculation.

Result 14
Uncertainty 0.5385

Formula: Add/sub: √(δa²+δb²); Mul/div: relative errors combine

Step-by-step with your numbers:
1. Values used:
2. Value A = 10
3. Uncertainty in A = 0.5
4. Value B = 4
5. Uncertainty in B = 0.2
6.
7. Result = 14
8. Uncertainty = 0.5385
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Uncertainties combine differently for sums than for products.

How the Math Works

The Error Propagation Calculator uses two fundamental formulas to combine measurement uncertainties. When adding or subtracting values (e.g., calculating total distance from multiple segments), absolute uncertainties combine in quadrature: √(δa²+δb²). For multiplication or division (e.g., calculating area from length × width), relative uncertainties (δa/a and δb/b) combine similarly: √((δa/a)² + (δb/b)²). This ensures that errors propagate realistically through calculations, preserving the statistical independence of measurements.

Practical Applications

To apply this calculator, first identify whether your calculation involves addition/subtraction or multiplication/division. Input the absolute uncertainties (δa, δb) for each measurement. For addition/subtraction, the calculator directly combines these using the quadrature formula. For multiplication/division, it first converts absolute uncertainties to relative errors, combines them, then scales back to the result's absolute uncertainty. This is essential in physics experiments, engineering tolerances, or financial modeling where multiple uncertain inputs affect a final outcome.

Day-to-Day Use

This tool helps in everyday scenarios where precision matters, such as cooking (adjusting recipe quantities with measuring cup tolerances), home improvement projects (calculating material needs from dimensions with tape measure errors), or fitness tracking (combining stride length and step count uncertainties for distance estimation). It also aids in evaluating product specifications, where combining component tolerances ensures final products meet safety or performance standards. By quantifying uncertainty, you make more informed decisions with imperfect measurements.

Worked example

(10 ± 0.5) + (4 ± 0.2) → 14 ± 0.54.

FAQ

Why add in quadrature?

Independent random errors partially cancel, so they add as a root-sum-of-squares.