Uncertainty Propagation in Fractional Expressions

In summary, the equation for e_f is f^2(\frac{e_u(u+v)}{u^2v}+\frac{e_v(u+v)}{v^2u}+\frac{e_u+e_v}{uv})
  • #1
Oerg
352
0

Homework Statement


Given that [tex] f=\frac{\bar u \bar v}{\bar u +\bar v}[/tex]

show that

[tex]e_f=f^2({\frac{e_u}{\bar u^2} + \frac{e_v}{\bar v^2}) [/tex]

where [tex]e[/tex] refers to the error. ok so I added up the fractional uncertainties

Homework Equations





The Attempt at a Solution


and I got this

[tex]\frac{e_f}{f}=\frac{e_u}{u}+\frac{e_v}{v}+\frac{e_u+e_v}{u+v}[/tex]

after some simplifying, I got to this,

[tex]e_f=f^2(\frac{e_u(u+v)}{u^2v}+\frac{e_v(u+v)}{v^2u}+\frac{e_u+e_v}{uv})[/tex]

and then I realized that I could never get the answer, however, if this term was negative,
[tex]\frac{e_u+e_v}{uv}[/tex], i would get the answer perfectly, but how can it be negative? Problem is even in division, shouldn't the fractional uncertianties add up??
 
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  • #2
any help?
 
  • #3
e_f is the maximum error, I have no idea why the term should be negative
 
  • #4
f(u,v)

df=(df/du)du+(df/dv)dv

I didn't notate it properly, but the derivatives are partial derivatives. Treat df as ef, du as eu, dv as ev
 
  • #5
Im sorry, I don't understand your post. how is my working affected by this equation?
 
  • #6
I don't follow your working at all, so I'm not sure if it's a right way that I don't know about.

Are you familiar with differentiation?
 
  • #7
yeh but not with partial derivatives,

What I did was to add up the fractional uncertainties.

I tried evaluating your equation, but I arrived at an ugly equation that doesn't fit the final bill.
 
  • #8
Oerg said:
yeh but not with partial derivatives,

What I did was to add up the fractional uncertainties.

I tried evaluating your equation, but I arrived at an ugly equation that doesn't fit the final bill.

OK, that's good. Partial differentiation is exactly like ordinary differentiation. So for examle df(u,v)/du just means normal differentiation of f with respect to u, holding v constant. It may look ugly, but it should work out.

So first evaluate df(u,v)/du.
 
  • #9
ok, I tried working out the coefficient of e_u according to your equation. Which is the partial derivative of f wrt u.

[tex]\frac{df}{du}=\frac{-uv}{(u+v)^2}+\frac{v}{u+v}[/tex]

unfortunately, it evaluaes out to be

[tex] f \times (\frac{v}{u(u+v)})[/tex]

which isn't what the question asked for. Have I differentiated wrongly?
 
  • #10
Try a different rearrangement, maybe take the common denominator to be (u+v)2
 
  • #11
I have already combined the two terms in my previous post, but i got [tex]f \times (\frac{v}{u(u+v)}) [/tex] for the coefficient of [tex]e_u[/tex] when it should have been
[tex] \frac{f}{u^2}[/tex]
 
  • #12
ok sorry, i got the answer, i have to factorise another f out again. THANKS FOR YOUR TIME, IM VERY VERY GRATEFUL!
 
  • #13
Wait - you have to do it for df(u,v)/dv also!
 
  • #14
yeh it's the same for the other term, it should evaluate out to be the same.
 
  • #15
And you understand what I meant in #4?
 
  • #16
yeh i do,

df=partial derivative of f wrt u times du + partial derivative of f wrt v times dv

\

from df du and dv to ef eu and ev is an approximation for a small change.
 
  • #17
OK, great (assuming what I said is correct :rolleyes:) :smile:
 

What is the concept of "Propagation of uncertainties"?

"Propagation of uncertainties" is a statistical method used to estimate the uncertainty or error in a calculated value that is derived from measured or estimated variables. It takes into account the uncertainties in the individual variables to determine the overall uncertainty in the final calculated value.

How is "Propagation of uncertainties" different from standard error?

"Propagation of uncertainties" is a more comprehensive approach to estimating error as it considers the uncertainties in all variables involved in the calculation, while standard error only takes into account the variability of the data points.

What are the assumptions made in "Propagation of uncertainties"?

The main assumptions in "Propagation of uncertainties" are that the individual variables are independent, and that the errors or uncertainties follow a normal distribution. It also assumes that the errors in the individual variables are small compared to their values.

How is "Propagation of uncertainties" calculated?

The calculation of "Propagation of uncertainties" involves using the partial derivative of the calculated value with respect to each variable, multiplied by the uncertainty in that variable. These values are then squared, summed, and the square root is taken to obtain the overall uncertainty.

Why is "Propagation of uncertainties" important in scientific research?

"Propagation of uncertainties" is important because it provides a more accurate estimate of the uncertainty in a calculated value, taking into account the variability and uncertainties in all the variables involved. This allows for a better understanding of the reliability and significance of the results, and helps in making informed decisions based on the data.

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