Calculating Error in Linearized Data: What is the Method?

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Homework Help Overview

The discussion revolves around calculating error for linearized data derived from a square root transformation. The original poster is attempting to understand how to determine the error associated with a transformed variable based on its uncertainty.

Discussion Character

  • Exploratory, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • The original poster debates between two methods for calculating error: converting original uncertainty to percent uncertainty and applying it directly, or manipulating the percent uncertainty further before applying it to the linearized data.

Discussion Status

Participants have engaged in clarifying the notation and methodology for calculating uncertainty. Some have provided specific formulas and examples, while others have confirmed their understanding through comparison of results. There appears to be a productive exchange of ideas regarding the application of derivatives in error calculation.

Contextual Notes

Participants are working under the constraints of a lab assignment, which may impose specific requirements for error calculation methods. The discussion includes varying interpretations of how to apply the uncertainty formulas correctly.

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Homework Statement


I'm doing a lab and I'm having difficulty calculating error for a linearized set of data. I need to find the error for a set of data that has been curved to a square root. for example my x= 5.00 +- .02 becomes sqrt(5) but what is the error?


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The Attempt at a Solution



I am debating whether to convert the original uncertainty to percent uncertainty and just multiply that by the linearized data or to convert the original uncertainty to percent uncertainty, square root the percentage and then multiply that by the linearized data.
 
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Let us denote the new quantity, y, which is a function of whatever variables you may have, x_1, x_2, x_3..., which have their respective uncertainties \Delta x_1, \Delta x_2, \Delta x_3...

Then the uncertainty in y is given by the formula:

\Delta y = \sqrt{(\frac{\partial y}{\partial x_1}\cdot \Delta x_1)^2+(\frac{\partial y}{\partial x_2}\cdot \Delta x_2)^2+(\frac{\partial y}{\partial x_3}\cdot \Delta x_3)^2+...}
 
so for my example point 5.00 +- .02 then y=\sqrt{\left(\frac{\sqrt{5}}{5}\times\frac{.02}{5.00}\right)^{2} = 2.2361 \pm .0018 (ignoring sig figs)?
 
No no, \frac{\partial y}{\partial x} means to take the partial derivative of y with respect to x (That means taking the derivative with respect to x, while treating every other parameter as constant)

So in your case, y=\sqrt{x}=x^{1/2}
\frac{\partial y}{\partial x}=\frac{1}{2\sqrt{x}}

Now that you know what the notation means, try and find the error.

My result is 2.2360±0.0044, if you want to compare.
 
Oh I didn't realize those were d's. so it is \sqrt{\left(\frac{1}{2\sqrt{5}}\times.02\right)^{2}}
I get 2.2360±0.0044 as well. I see how it works. Thank you for your help!
 
Sure thing. :) Just try and keep the general formula in mind, since eventually you'll have to deal with errors in quantities like:

z=\sqrt{x+y}
\Delta x=5.00\pm 0.02
\Delta y=6.00\pm 0.03

See if you can find \Delta z
My answer is: ±0.0054
 

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