Relative error and measurement precision

In summary: So, you need to solve for ##A##.In summary, the goal is to find the right amount of relative error on x to obtain a 1% precision on y. The function is y=\sqrt{(x_{1}-x_{1,c})^{2}+(x_{2}-x_{2,c})^{2}}, and one of the coordinates has no error while the other has a relative error. To calculate precision, one would use the same formula of relative error, but I'm not sure.
  • #1
mPlummers
12
1
Homework Statement
I have a data point ##x_{true}##, without error. I also have a function ##f(x_{true})=y_{true}##. I have to obtain a simulated measurement, adding to this data point a relative error (and so i'll pass from ##x_{true}## to a ##x_{measurement}##). The goal is to find the amount of relative error to add to ##x_{true}## to obtain a measurement of ##y_{measurement}## with 1% precision.
Relevant Equations
Relative error: ##(y_{true}-y_{measurement})/y_{measurement}##
NOTE: this is a programming exercise (Python).
I started adding to ##x_{true}## an error related to a (for example) 10% relative error, obtaining ##x_{measurement}##. Then i computed ##y_{measurement}##. To find the precision, i calculated ##(y_{true}-y_{measurement})/y_{measurement}##. If it is correct, what i want to do is to use several relative error values, compute the precision and look for the closest to 1%.
 
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  • #2
If I understand the problem, your goal is to be able to produce y values with a 1% relative error. Your challenge is to find a distribution of x values that result in y values that satisfy this criterion.

Question: does the graph of f() have a reasonably constant slope in the neighborhood of ##(x_{true},y_{true})##. More specifically in the neighborhood where ##.99\ y_{true} < y < 1.01\ y_{true}##?
 
  • #3
Yes, the goal is to find the correct amount of relative error on ##x_{meas}## to obtain a 1% precision on ##y_{meas}##. The teacher told us that this is the inverse problem of finding the right instrument (in terms of precision) depending on the relative error you want to obtain. The function is ##y=\sqrt{(x_{1}-x_{1,c})^{2}+(x_{2}-x_{2,c})^{2}}##, it returns the radius of a circle, given the center coordinates. One of the coordinate doesn't have any error, while the other one is the ##x## i mentioned in the first post. How can i calculate the precision? I used the same formula of relative error, but I'm not sure.
 
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  • #4
mPlummers said:
Yes, the goal is to find the correct amount of relative error on ##x_{meas}## to obtain a 1% precision on ##y_{meas}##. The teacher told us that this is the inverse problem of finding the right instrument (in terms of precision) depending on the relative error you want to obtain. The function is ##y=\sqrt{(x_{1}-x_{1,c})^{2}+(x_{2}-x_{2,c})^{2}}##, it returns the radius of a circle, given the center coordinates. One of the coordinate doesn't have any error, while the other one is the ##x## i mentioned in the first post. How can i calculate the precision? I used the same formula of relative error, but I'm not sure.
I assume you mean you are given the centre exactly and a circumferential point approximately. This is not quite the same as in post #1 since you now have two uncertain values... or is one coordinate of the point on the circumference known exactly too?
 
  • #5
Exactly, one of the point coordinates has no error, while the other one has a relative error. That's why in the first post i simplified the problem from 2D to 1D . In the second post i wrote the real problem to show the function i have to use.
 
  • #6
mPlummers said:
Exactly, one of the point coordinates has no error, while the other one has a relative error. That's why in the first post i simplified the problem from 2D to 1D . In the second post i wrote the real problem to show the function i have to use.
Ok.
Replace x2 in your expression for y with x2(1+ε). Apply a Taylor expansion to get it into the form ##\sqrt{(x_{1}-x_{1,c})^{2}+(x_{2}-x_{2,c})^{2}}(1+A\epsilon+...)##.
 
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Related to Relative error and measurement precision

What is relative error?

Relative error is a measurement of the accuracy of a measurement compared to the true or expected value. It is the ratio of the absolute error (the difference between the measured value and the expected value) to the expected value. It is typically expressed as a percentage or decimal.

How is relative error different from absolute error?

Absolute error is the difference between the measured value and the expected value, while relative error takes into account the magnitude of the expected value. This means that relative error can be used to compare the accuracy of measurements with different scales or units, while absolute error cannot.

What is measurement precision?

Measurement precision refers to the level of consistency or reproducibility in a set of measurements. It is determined by the smallest unit of measurement used and the level of detail in the measurement. Higher precision means that the measurements have less variability and are closer in value to each other.

How is precision related to relative error?

Precision and relative error are inversely related. This means that as the precision of a measurement increases, the relative error decreases. This is because a more precise measurement has less variability and is closer to the true value, resulting in a smaller relative error.

What factors can affect the relative error and precision of a measurement?

The accuracy and precision of a measurement can be affected by a variety of factors, including the quality of the measuring instrument, human error, environmental conditions, and the level of detail in the measurement. It is important to control these factors as much as possible to ensure accurate and precise measurements.

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