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Percent error and uncertainty propagation calculator

Percent error from measured and accepted values, and uncertainty propagation through sums, products, quotients and powers, in quadrature or worst case.

Atualizado Exemplos verificados: 7

Experimentar
Percent error
%
Percent error: 0.9174 %
Máximo de casas decimais: 4; Ao mais próximo; empates afastando-se de zero
Signed percent error
−0.9174%
Absolute error
0.09

The measurement is 0.9174% below the accepted value.

Signed percent error (0 = the accepted value)

over 5% low1–5% low1–5% highover 5% high-10-5-11510accepted−0.9174%
Como é calculado S

  1. Difference from the accepted value

    xm−xa=9.72−9.81=−0.09x_m - x_a = 9.72 - 9.81 = -0.09

  2. Percent error

    ∣−0.09∣∣9.81∣×100=0.917431%\frac{|-0.09|}{|9.81|}\times100 = 0.917431\%

Sobre Percent error and uncertainty propagation calculator

Percent error compares a measurement with an accepted value: |measured − accepted| / |accepted| × 100. Uncertainty propagation works out how the ± uncertainties of inputs carry into a calculated result. For sums and differences the absolute uncertainties combine; for products and quotients the relative uncertainties combine; a power aⁿ multiplies the relative uncertainty by |n|. Independent random errors combine in quadrature (the square root of the sum of squares), and the worst-case option adds them linearly.

The default, a measured g of 9.72 m/s² against the accepted 9.81 m/s², is 0.917% low. Multiplying (2.0 ± 0.1) by (3.0 ± 0.2) gives relative uncertainties of 5% and 6.7%, which combine in quadrature to 8.3%, so the product is reported as 6.0 ± 0.5.

Results are rounded as Taylor's An Introduction to Error Analysis recommends: the uncertainty to one significant figure, or two when it starts with 1, and the value to the same decimal place. The formulas are first-order, so they assume each uncertainty is small compared with its value.

Exemplos resolvidos

Measured g = 9.72 against 9.81

Calculate
Percent error
Measured value
9.72
Accepted (true) value
9.81
Percent error
0.9174%
Signed percent error
-0.9174%
Absolute error
0.09

Fonte de verificação: Python 3.8 decimal: |9.72 − 9.81| / 9.81 × 100 = 0.9174312

Sum in quadrature: (10.0 ± 0.3) + (5.0 ± 0.4)

Calculate
Sum or difference a ± b
Operation
a + b or a × b
a
10.0
Uncertainty in a (±)
0.3
b
5.0
Uncertainty in b (±)
0.4
Combine uncertainties
In quadrature
Result q
15
Uncertainty δq
0.5
Report as
15.0 ± 0.5

Fonte de verificação: Taylor §3.5: √(0.3² + 0.4²) = 0.5

Same sum, worst case

Calculate
Sum or difference a ± b
Operation
a + b or a × b
a
10.0
Uncertainty in a (±)
0.3
b
5.0
Uncertainty in b (±)
0.4
Combine uncertainties
Worst case
Uncertainty δq
0.7
Report as
15.0 ± 0.7

Fonte de verificação: Taylor §3.3: δa + δb = 0.7

Product (2.0 ± 0.1) × (3.0 ± 0.2)

Calculate
Product or quotient a × b, a ÷ b
Operation
a + b or a × b
a
2.0
Uncertainty in a (±)
0.1
b
3.0
Uncertainty in b (±)
0.2
Combine uncertainties
In quadrature
Result q
6
Uncertainty δq
0.5
Report as
6.0 ± 0.5

Fonte de verificação: Python 3.8 decimal: 6 × √(0.05² + 0.0667²) = 6 × 0.083333 = 0.5

Perguntas

How do you calculate percent error?

Percent error = |measured − accepted| / |accepted| × 100. Measuring g as 9.72 m/s² against an accepted 9.81 m/s² gives 0.09/9.81 × 100 = 0.917%. Keep the sign when the direction matters: −0.917% says the measurement came out low. The formula fails when the accepted value is 0; report the absolute error instead.

How do you propagate uncertainty when multiplying or dividing?

Combine the relative uncertainties in quadrature: δq/|q| = √((δa/a)² + (δb/b)²). For (2.0 ± 0.1) × (3.0 ± 0.2) the relative uncertainties are 5% and 6.7%, giving 8.3% of 6.0, so q = 6.0 ± 0.5. Division follows the same rule: (10 ± 0.5) ÷ (4 ± 0.2) = 2.50 ± 0.18.

How do you add or subtract uncertainties?

Combine the absolute uncertainties: δq = √(δa² + δb²) when the errors are independent and random, or δa + δb for a worst-case bound. (10.0 ± 0.3) + (5.0 ± 0.4) = 15.0 ± 0.5 in quadrature, or 15.0 ± 0.7 worst case. Subtraction uses the same rule, so the difference of two close values can carry a large relative uncertainty.

When should uncertainties be added in quadrature?

When the errors in the inputs are independent and random, the assumption behind the combined standard uncertainty in NIST Technical Note 1297 and the GUM. Quadrature never exceeds the linear sum: 0.3 and 0.4 combine to 0.5 rather than 0.7. Use the linear worst case when errors may be correlated, such as two readings taken with the same miscalibrated instrument.

How many significant figures should an uncertainty have?

One, or two when its leading digit is 1, following Taylor's An Introduction to Error Analysis (§2.2); the value is then rounded to the same decimal place. So 0.1768 becomes 0.18 and the result is written 2.50 ± 0.18, while 0.52 becomes 0.5 and the result 6.0 ± 0.5. Writing 6.0 ± 0.5234 claims more precision than the measurement has.

Qual é a precisão de “Percent error and uncertainty propagation calculator”?

A precisão depende dos dados inseridos e das hipóteses do método. O cálculo decimal usa 50 algarismos significativos, mas estimativas, métodos numéricos e dados de origem podem ter menor precisão; o arredondamento exibido não elimina essas limitações. Exemplos resolvidos verificados com fontes independentes: 7. Por exemplo, “Measured g = 9.72 against 9.81” é verificado com Python 3.8 decimal: |9.72 − 9.81| / 9.81 × 100 = 0.9174312.

De onde vem o método?

Taylor, An Introduction to Error Analysis (2nd ed., 1997), ch. 2–3 (rules for reporting and propagating uncertainties); NIST Technical Note 1297 — Guidelines for evaluating and expressing the uncertainty of NIST measurement results.

Sobre esta calculadora

% error=∣xm−xa∣∣xa∣×100;δ(a±b)=δa2+δb2;δ(ab)∣ab∣=(δaa)2+(δbb)2;δ(an)∣an∣=∣n∣δa∣a∣\%\,\text{error} = \frac{|x_m - x_a|}{|x_a|}\times100;\quad \delta(a\pm b) = \sqrt{\delta a^2 + \delta b^2};\quad \frac{\delta(ab)}{|ab|} = \sqrt{\Big(\frac{\delta a}{a}\Big)^2 + \Big(\frac{\delta b}{b}\Big)^2};\quad \frac{\delta(a^n)}{|a^n|} = |n|\frac{\delta a}{|a|}

Fontes

  1. Taylor, An Introduction to Error Analysis (2nd ed., 1997), ch. 2–3 (rules for reporting and propagating uncertainties)
  2. NIST Technical Note 1297 — Guidelines for evaluating and expressing the uncertainty of NIST measurement results

Verificado com as referências

Esta calculadora inclui 7 exemplos resolvidos com respostas de fontes independentes. Eles fazem parte do conjunto de testes e você também pode executá-los aqui.

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