I Error Propagation (Percentage) - sin(x)^2 / x^2

AI Thread Summary
The discussion focuses on propagating percentage errors in the equation y = sin(x)^2 / x^2, particularly when both errors originate from the same source. It clarifies that converting absolute errors to percentage errors is essential for accurate calculations. The method involves using derivatives to relate changes in y to changes in x, allowing for the calculation of error in y based on the known error in x. The conversation emphasizes that these formulas are approximative and most effective for small relative errors. Understanding and applying these principles ensures accurate error propagation in complex equations.
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Hey, I'm trying to propagate my percentage errors through some hefty equations and come up on a bit of snag:

I've got a percentage error for x and know how to deal with it for trig functions and powers, however since both errors are from the same source:

y = sin(x)^2 / x^2

Should I just simplify it to: 2*error
 
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What do you mean by percentile errors? Do you mean you have something like the 25th percentile, 50th percentile (median), and 75th percentile of x?
 
Sorry, I just mean that I've converted the error, from absolute to percentage beforehand. I've just edited my original post to fix the mistake.
 
If the errors are small, then you can take the derivative of both sides of the equation. You get something of the form
dy = (...) dx
then just plug your error into dx, and then dy will be your error in y.
 
As Khashishi said, it is something like: dy = y'(x) dx, where dx, dy are absolute deviations. Relative deviations are dx/x, dy/y:

dy/y(x) = y'(x)/y(x) * x * dx/x

Here x,y,y(x),y'(x) should be computed for x=reference value of x (the one supposedly without errors).

If you take errors dx, dy to be standard deviations, then relative errors would be:

dy/|y(x)| = | y'(x)/y(x) * x | * dx/|x|

and x should be the average value of x. Relative errors can be expressed in % (of the average values). Formulas are approximative and work for a small relative error in x.
 
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