Talk:Propagation of uncertainty

Derivative is not partial in Example calculation: Inverse tangent function

If $f(x)=\arctan(x)$ then you cannot take ${\frac {\partial f}{\partial x}}$, because $f$ only depends on one variable. It should be ${\frac {df}{dx}}$ — Preceding unsigned comment added by Finkeltje (talk • contribs) 15:31, 1 February 2013 (UTC)

It's been fixed already. Feel free to correct the page directly instead of just reporting it. Fgnievinski (talk) 18:38, 2 November 2014 (UTC)

True, but it would actually be more instructive in this article to use the partials to provide the propagated error of arctan(y/x) where the standard deviations of x and y are known or estimated. 193.17.11.20 (talk) 14:23, 17 September 2018 (UTC)

Linear Combinations section had following formula:

$\sigma _{f}^{2}=\sum _{i}^{n}\sum _{j}^{n}a_{i}\Sigma _{ij}^{x}a_{j}=\mathbf {a\Sigma ^{x}a^{t}}$

I changed this to

$\sigma _{f}^{2}=\sum _{i}^{n}\sum _{j}^{n}a_{i}\Sigma _{ij}^{f}a_{j}=\mathbf {a\Sigma ^{f}a^{t}}$

Can we please not have a single equation where a single sign is both a variable and an operator ? It almost seems like someone want to make it unclear on purpose — Preceding unsigned comment added by 128.252.25.45 (talk) 21:48, 5 February 2019 (UTC)

f=aA^b is incorrect

The example for f=aA^+/-b is incorrect. The derivation which gives this result is based on the f=AB example used b-1 times. However the f=AB example assumes A and B are independent. When considering powers they are not. Instead for positive b we need to do a binomial expansion of f+σ_f=a(A+σ_A)^b and discard all terms with powers of σ_A greater than 1, because they should be negligible (assuming the uncertainty is small compared to the absolute value). This gives σ_f = abA^b-1σ_A = abfσ_A/A. For negative b we again start with f+σ_f=a(A+σ_A)^b, then we split it as f+σf= aA^b(1+σ_A/A)^b. We can then expand this as per http://mathworld.wolfram.com/NegativeBinomialSeries.html, to give f+σf=aA^b(1+bσ_A/A), again assuming terms with σ_A to the power two or more are negligible. substituting in for f and rearranging gives σ_f=abA^b-1σ_A - the same result as for positive b!

I have not yet made the change to the page but I will if nobody objects

Philrosenberg (talk) 14:30, 16 September 2014 (UTC)

Note also that the derivative of A^b is not bA^b-1 but ln(A)A^b (https://en.wikipedia.org/wiki/Derivative). — Preceding unsigned comment added by 193.136.48.112 (talk) 09:07, 5 August 2015 (UTC)

Propagation of errors resulting from algebraic manipulations

Propagation of errors resulting from algebraic manipulations, currently a redirect to this page, has been nominated for deletion. The discussion at Wikipedia:Redirects for discussion/Log/2017 April 16#Propagation of errors resulting from algebraic manipulations needs input from those with knowledge of the subject. Thryduulf (talk) 13:38, 17 April 2017 (UTC)

Why don't we include this figure in the article?

This scheme depicts the idea behind the formula for the propagation of error $\Delta x$. $\Delta y_{\pm }$ are the true uncertainties in y which are present for an uncertainty $\pm \Delta x$. $\pm \Delta y$ are the uncertainties which are calculated based on the linear approximation.

The figure was recently removed without explaination. 2A01:C23:783B:B600:B48D:E0C5:7819:B0DD (talk) 10:52, 10 January 2020 (UTC)