Progation of error in this formula

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The discussion focuses on calculating the uncertainty in the formula u = (1/(2LS))^2, given the uncertainties in L and S. Participants explain the process of using partial differentiation to evaluate the uncertainty, emphasizing that one should treat other variables as constants during differentiation. A step-by-step approach is provided, demonstrating how to derive partial derivatives and apply them in the uncertainty formula. The final calculation of uncertainty yields a result of 1.36 x 10^-4, with reassurance that the method will not produce an error smaller than the individual error components. The conversation highlights the importance of understanding partial differentiation in error analysis.
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Hi,

u = (1/(2LS))^2

L = .9810 +/- 0.0005
S = 8.35 +/- 0.15

Can anyone give me the formula to calculate the uncertainity on u.
 
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(\delta u)^2 = (\frac{\partial u}{\partial L} \delta L)^2+ (\frac{\partial u}{\partial S} \delta S )^2
 
Thanks but a very similar formula is given in my lab manual, but I don't know partial differentiation. So, how would i actually evaluate the uncertainty.
 
Do you know how to do regular differentiation?
 
ya... I am pretty sure uncertainities are evaluated using partial differentation
 
just regard it as orinary derivative
for

\frac{\partial u}{\partial L}

take S as constant and L as independent variable, and do

\frac{d u}{d L}
 
Given a function U=x^2+y^2+2xy.

To find the partials simply pretend the other variables are simply constants:

\frac{\partial U}{\partial x}=\frac{\partial}{\partial x}(x^2+y^2+2xy)

So, looking at the above y^2 will act as a constant. The derivative of a constant is zero so \frac{\partial}{\partial x}y^2=0.

Using that logic:

\frac{\partial U}{\partial x}=\frac{\partial}{\partial x}(x^2+y^2+2xy)=2x+0+2y

Or simply

\frac{\partial U}{\partial x}=2x+2y
 
vincentchan said:
(\delta u)^2 = (\frac{\partial u}{\partial L} \delta L)^2+ (\frac{\partial u}{\partial S} \delta S )^2


Thanks for all your help so far, but I will leave partials to next year calc... Can you guys simplify this for me
 
It's easy to do. Just follow the steps I supplied in my above post. Pretend the other variables are constants and perform differentiation (just like regular except only one one variable with the others held constant) on the equation. Repeat this until all variables have been differentiated.

It's not hard, don't let the fact that you haven't had calc III scare you from this concept.
 
  • #10
Here: I'll do more work to show you how to do this rather than simply give you the answer...

\delta x=0.1 This is the error in x
\delta y=0.05 This is the error in y

x=10--value found during an experiment.
y=20--value found during an experiment.

U=x^3+3x^2y+3y^2x+y^3

the partial of the above (with y magically transformed into a constant) would be:

\frac{\partial U}{\partial x}=(3)x^2+(6y)x+(3y^2)+0

I put () around all of the constants in the final expression.

\frac{\partial U}{\partial y}=0+(3x^2)+(6x)y+(3)y^2

So, the error in U would be:

U_{error}=\sqrt{(\frac{\partial U}{\partial x}\delta x)^2+(\frac{\partial U}{\partial y}\delta y)^2}

which when we substitute the partials into the error eqn yields:


U_{error}=\sqrt{([(3)x^2+(6y)x+(3y^2)]\delta x)^2+([(3x^2)+(6x)y+(3)y^2]\delta y)^2}

Plug in the numeric values for x/y and the errors:

U_{error}=\sqrt{([(3)10^2+(6\cdot 20)10+(3\cdot 20^2)]0.1)^2+([(3\cdot 10^2)+(6\cdot 10)20+(3)20^2]0.05)^2}

Plug the above into a calculator and you'll get something greater than the largest single value of error (you will never get a total error smaller than anyone of the error components.

Hope this helped.
 
  • #11
Thanks, your post is really helpful... I don't know how to use latex but I got the final error as 1.36 x 10-4 .. Hopefully I did it right :smile:
 
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