Progation of error in this formula

In summary, the uncertainty on u is evaluated using partial differentiation. The error in u is found by solving for the partial of the equation with y held constant.
  • #1
thegame
32
0
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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  • #2
[tex] (\delta u)^2 = (\frac{\partial u}{\partial L} \delta L)^2+ (\frac{\partial u}{\partial S} \delta S )^2 [/tex]
 
  • #3
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.
 
  • #4
Do you know how to do regular differentiation?
 
  • #5
ya... I am pretty sure uncertainities are evaluated using partial differentation
 
  • #6
just regard it as orinary derivative
for

[tex]\frac{\partial u}{\partial L}[/tex]

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

[tex]\frac{d u}{d L}[/tex]
 
  • #7
Given a function [itex]U=x^2+y^2+2xy[/itex].

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

[tex]\frac{\partial U}{\partial x}=\frac{\partial}{\partial x}(x^2+y^2+2xy)[/tex]

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

Using that logic:

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

Or simply

[tex]\frac{\partial U}{\partial x}=2x+2y[/tex]
 
  • #8
vincentchan said:
[tex] (\delta u)^2 = (\frac{\partial u}{\partial L} \delta L)^2+ (\frac{\partial u}{\partial S} \delta S )^2 [/tex]


Thanks for all your help so far, but I will leave partials to next year calc... Can you guys simplify this for me
 
  • #9
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...

[itex]\delta x=0.1[/itex] This is the error in x
[itex]\delta y=0.05[/itex] This is the error in y

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

[tex]U=x^3+3x^2y+3y^2x+y^3[/tex]

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

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

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

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

So, the error in U would be:

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

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


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

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

[tex]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}[/tex]

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 :rofl:
 

What is the formula for propagation of error?

The formula for propagation of error is used to determine the uncertainty or error in a calculated value based on the uncertainties or errors in the measured values used in the calculation. It is expressed as ∆Z = √( (∂Z/∂X)^2 * ∆X^2 + (∂Z/∂Y)^2 * ∆Y^2 + ...), where Z is the final calculated value, X and Y are the measured values, and ∆X and ∆Y are the respective uncertainties or errors.

Why is propagation of error important?

Propagation of error is important because it allows scientists to quantify the uncertainty in a calculated value and to determine the reliability of their results. It also helps in identifying the sources of error in a measurement or calculation, which can aid in improving experimental techniques.

What are the assumptions made in propagation of error?

The assumptions made in propagation of error are that the errors in the measured values are independent and random, and that the errors are small compared to the measured values. Additionally, the errors should follow a normal distribution.

What factors affect the magnitude of error in propagation of error?

The magnitude of error in propagation of error is affected by the uncertainties or errors in the measured values, as well as the sensitivity of the calculated value to changes in the measured values. The more sensitive the calculated value is to changes in the measured values, the larger the error will be.

Can propagation of error be used for any type of calculation?

Propagation of error can be used for any type of calculation, as long as the assumptions are met and the uncertainties or errors in the measured values are known. However, it may be more difficult to use for complex calculations or those involving non-linear relationships between variables.

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