How to calculate the propagation error for a tricky Eq

In summary: The error in alpha will be about 167 times the sum of the percents. You need to recognize the difference between these ratios and the raw products.In summary, the speaker is trying to calculate the propagation error for a function alpha that involves the measurements of i1, i2, g1, g2, t1, and t2. They have attempted to use classical error propagation, but are unsure if it is correct. When given values for these measurements, the error in alpha is calculated to be around 1000%, which the speaker believes is too large. After further discussion, it is determined that the error is being amplified due to the small difference between the ratios in the function, causing the error in alpha to
  • #1
andresfirman
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Moved from a technical forum, so homework template missing
Hello Please help me, my function is;

alpha = [ i1.g2 / (i2.g1) - 1 ] / ( t1-t2 )

I will have to measure i1, i2, g1, g2, t1 and t2 them
I made classical error porpagation, but I don't know if this is ok.

How is the proper way to calculate the propagation error for alpha?
 
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  • #2
andresfirman said:
Hello Please help me, my function is;

alpha = [ i1.g2 / (i2.g1) - 1 ] / ( t1-t2 )

I will have to measure i1, i2, g1, g2, t1 and t2 them
I made classical error porpagation, but I don't know if this is ok.

How is the proper way to calculate the propagation error for alpha?
Hello andresfirman, :welcome:

PF culture encourages you to set up some attempt before assistance is given.
What is the general formula for error propagation that you are using ?
 
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  • #3
BvU said:
Hello andresfirman, :welcome:

PF culture encourages you to set up some attempt before assistance is given.
What is the general formula for error propagation that you are using ?
Hi, I`m using

d(alpha)/d(i1)*Δi1 + d(alpha)/d(i2)*Δi2 + d(alpha)/d(g1)*Δg1 + d(alpha)/d(g2)*Δg2 + d(alpha)/d(t1)*Δt1 + d(alpha)/d(t2)*Δt2

Δi1 = 0.3 %
Δi2 = 0.3 %
Δg1 = 3.2 %
Δg2 = 3.2 %
Δt1 = 0.2 C
Δt2 = 0.2 C

Its values aprox are;
t1 and t2 is near 26 C
g1 and g2 is near 950
and i1 and i1 are near 7.5

it give me aprox 1000 % of error its too big I think, I don't know where is the problem. I don't think that the quantities errors are too big for the answer of 1000 %
 
  • #4
andresfirman said:
t1 and t2 is near 26 C
But how near are they to each other? When you take differences of numbers of similar size the error percentage can get hugely magnified.
Same issue arises with i1.g2-i2.g1.
 
  • #5
haruspex said:
But how near are they to each other? When you take differences of numbers of similar size the error percentage can get hugely magnified.
Same issue arises with i1.g2-i2.g1.
Hi!;
t1 = 27.6 C
t2 = 44.9 C
g1 = 993
g2 = 1000
i1 = 7.5
i2 = 7.6

so, alpha is a very low number
alpha = 0.0003766
 
  • #6
andresfirman said:
g1 = 993
g2 = 1000
i1 = 7.5
i2 = 7.6
There's a problem. The ratio of the products, as in your equation, differs from 1 by only 0.6%. That effectively amplifies the error percentage by 1/0.006= 167.
 

Related to How to calculate the propagation error for a tricky Eq

1. How do I calculate the propagation error for a tricky equation?

To calculate the propagation error for a tricky equation, you will need to first determine the individual errors for each variable in the equation. These errors can be determined through measurement or by using the estimated error for each variable. Once you have the individual errors, you can use the formula for propagation of error to calculate the overall propagation error for the equation.

2. What is the formula for propagation of error?

The formula for propagation of error is: σ_f = √(∑(∂f/∂x_i)^2σ_i^2) where σ_f is the propagation error for the final result, ∂f/∂x_i is the partial derivative of the function with respect to each variable, and σ_i is the error for each variable.

3. Is it necessary to calculate propagation error for every equation?

It is not necessary to calculate propagation error for every equation. This method is mainly used for equations with multiple variables and uncertainties, or when the final result is highly dependent on the individual errors of the variables. In some cases, a simpler error estimation method may suffice.

4. Can propagation error be negative?

No, propagation error cannot be negative. It represents the uncertainty or range of values for the final result and therefore cannot be negative.

5. How can I reduce propagation error in my calculations?

Propagation error can be reduced by minimizing the individual errors for each variable in the equation. This can be achieved through more precise measurements or by using more accurate values for the variables. Additionally, using error propagation rules and methods for combining uncertainties can also help in reducing the overall propagation error.

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