Error propogation in trig functions

In summary, the student is trying to find the error in a function that takes the angle in degrees. The student is using the quadrature method to find the error, but is getting an error that is less than the number of significant digits. The student then realizes that the angle is in radians, and makes a correction. The student is then trying to find two angles that go along with θ being maximum and minimum, and average them to get the Δθs.
  • #1
richyw
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Homework Statement



I have to use this in my calculation [tex]\theta=\tan^{-1}\left(\frac{19 \pm 1}{47 \pm 1}\right)[/tex] where both are in mm. How would I get this into [itex]\theta\pm \text{error}[/itex]?

Homework Equations



shown above

The Attempt at a Solution



looked through my lab manual, it wasn't there.
 
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  • #2
ok I found this online

We can express the uncertainty in R for general functions of one or more observables. If R is a function of X and Y, written as R(X,Y), then the uncertainty in R is obtained by taking the partial derivatives of R with respect to each variable, multiplication with the uncertainty in that variable, and addition of these individual terms in quadrature.

[tex]R=R(X,Y,...)[/tex]
[tex]\delta R=\sqrt{\left(\frac{\partial R}{\partial X} \delta X\right)^2+\left(\frac{\partial R}{\partial Y}\delta Y\right)^2+...}[/tex]
 
  • #3
so if I say that the numerator there is x and the denominator is L, then I wind up with
[tex]\delta\theta=\frac{L\delta x + x\delta L}{L^2+x^2}[/tex]

would someone be able to let me know if this is correct?
 
  • #4
oops I made a mistake in the algebra. the formula I am getting is

[tex]\sqrt{ \left(\frac{L}{x^2+L^2}\delta x\right)^2+\left(-\frac{x}{x^2+L^2}\delta L\right)^2}[/tex]

I'm getting a very small error though. less than the number of significant digits. this seems a bit off...
 
  • #5
richyw said:
oops I made a mistake in the algebra. the formula I am getting is

[tex]\sqrt{ \left(\frac{L}{x^2+L^2}\delta x\right)^2+\left(-\frac{x}{x^2+L^2}\delta L\right)^2}[/tex]

I'm getting a very small error though. less than the number of significant digits. this seems a bit off...

That looks good to me. Are you expressing θ in radians?
 
  • #6
nope, it needs to be expressed in degrees. That simplfies to [tex]\frac{\sqrt{(L\delta x)^2 +(x\delta L)^2}}{L^2+x^2}[/tex] but it's giving me a value lower than the number of sig figs I have. what do I do now? haha
 
  • #7
is this my relative error? it comes out unitless...
 
  • #8
bumping this. I'm really confused as to what this error means physically.
 
  • #9
First, a 'soapbox' about the quadrature method. It's perfectly fine and appropriate if the input uncertainties represent some number of standard deviations (the same number in each case) of roughly normally and independently distributed measurements. The answer then represents the same number of s.d. of the output.
But it's not unusual in engineering and in lab work that the input uncertainties would be better modeled as hard limits of uniform distributions. If there are many such inputs, the best approach is probably to turn each of those into a specific number of standard deviations, use quadrature, and understand that whatever number of s.d. you chose applies to the answer. But with only two inputs, you might be better served simply considering the four extreme values generated by plugging in the extremes of the two input ranges. The resulting range won't represent a uniform distribution, more triangular perhaps, but it will give you hard limits, and in engineering that may be more relevant.
Wrt your working so far, the formula you used for derivative of arctan assumes the angle is in radians. If it's in degrees you'll need to make a correction for that. It should be dimensionless - because angles are dimensionless.
 
  • #10
Here's another possibility. θ is maximum with 20/46, and minimum with 18/48. Determine the two angles which go along with these, average them, and then find the (equal) deviations from the average. These are the Δθs.
 
  • #11
richyw said:
the formula I am getting is

[tex]\sqrt{ \left(\frac{L}{x^2+L^2}\delta x\right)^2+\left(-\frac{x}{x^2+L^2}\delta L\right)^2}[/tex]

I'm getting a very small error though. less than the number of significant digits. this seems a bit off...

The expression you derived is only valid if θ is measured in radians. When using the standard calculus formulas for derivatives of trig functions, the angles are assumed to be in radians. For example d(tanθ)/dθ = sec2θ assumes θ is in radians. So, your expression gives the error in θ measured in radians. You can then convert to degrees if you wish.
 
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FAQ: Error propogation in trig functions

What is error propagation in trig functions?

Error propagation in trig functions refers to the process of determining how uncertainties in the input values of a trigonometric function affect the uncertainty in the output value. It allows for the calculation of the error or uncertainty in the final result based on the errors in the individual input values.

Why is error propagation important in trigonometric calculations?

Trigonometric calculations often involve multiple steps and use various input values, each with their own uncertainties. By understanding how these uncertainties propagate through the trigonometric functions, we can have a better understanding of the overall accuracy and reliability of the final result.

How is error propagation calculated in trig functions?

Error propagation in trig functions is typically calculated using the formula for error propagation, which takes into account the partial derivatives of the trigonometric function with respect to each of the input values. This allows for the calculation of the overall uncertainty in the final result.

Can error propagation affect trigonometric identities?

Yes, error propagation can affect trigonometric identities. Because uncertainties in the input values can lead to uncertainties in the output values, this can result in slight variations in the values of trigonometric functions. These variations can then affect the accuracy of trigonometric identities.

How can error propagation in trig functions be minimized?

Error propagation in trig functions can be minimized by reducing the uncertainties in the input values as much as possible. This can be achieved through careful measurement techniques and the use of more precise instruments. Additionally, using trigonometric identities and simplifying calculations can also help reduce the overall error propagation.

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