Propagation of uncertainty in an experiment

In summary, the conversation discusses the uncertainty involved in calculating the distance between pits in a DVD using different wavelength lasers. The speaker took 9 measurements with their own uncertainties and calculated the average and standard deviation, but is unsure of how to combine the uncertainties. They suspect that taking the average of the uncertainties and adding it to the standard deviation may be a possible solution. They ask for help in understanding how to propagate uncertainty when averaging, and a resource is provided for reference. The conversation also mentions the calculation of a weighted mean and standard deviation for multiple data points.
  • #1
MeissnerEffect
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I performed an experiment using different wavelength lasers to calculate the distance between the pits of a DVD by measuring the angles formed by the resulting diffraction pattern,but now I'm unsure on how to calculate the uncertainty of the final result.

I took 9 measurements each with their own uncertainty, found an average and calculated the standard deviation, but I'm unsure of how I'm supposed to combine the uncertainties of each individual result with the standard deviation.

I suspect that I should do something like get the average of the uncertainties and add it to the standard deviation, although it's pretty much just a guess.

Can someone please help me(or at least link me a a resource) understand how to propagate uncertainty through an averaging?

Thank you
 
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  • #2
See http://ned.ipac.caltech.edu/level5/Leo/Stats4_5.html, for example.

If xi is the mean and σi is the standard deviation/uncertainty of the result of the i-th experiment, the weighted mean of n data is

[tex]\bar x = \frac{\sum_1^n {x_i/\sigma_i^2}}{\sum_1^n {1/\sigma_i^2}}[/tex]and the standard deviation/ uncertainity of the mean is

[tex]\bar\sigma =\sqrt{\frac{1}{\sum_1^n {1/\sigma_i^2}}}[/tex]

ehild
 

FAQ: Propagation of uncertainty in an experiment

1. How do you define uncertainty in an experiment?

Uncertainty in an experiment refers to the amount of doubt or lack of precision in the measurement or result of an experiment. It can be caused by various factors such as limitations of equipment, human error, and variations in the environment.

2. What is the difference between random and systematic uncertainty?

Random uncertainty arises from unpredictable variations in measurement, while systematic uncertainty is caused by a consistent error or bias in the experiment. Random uncertainty can be reduced by taking multiple measurements, while systematic uncertainty can be minimized by identifying and correcting the source of the error.

3. How is uncertainty propagated in an experiment?

Uncertainty is propagated in an experiment by using mathematical techniques such as error propagation formulas and Monte Carlo simulations. These methods take into account the uncertainties in the measured quantities and use them to calculate the overall uncertainty in the final result.

4. What is the importance of considering uncertainty in an experiment?

Considering uncertainty in an experiment is important because it provides a measure of the reliability and accuracy of the results. It also allows for proper interpretation of the data and helps in determining the significance of any differences between experimental and theoretical values.

5. Can uncertainty be completely eliminated in an experiment?

No, uncertainty cannot be completely eliminated in an experiment. It is a natural part of the scientific process and is always present to some degree. However, it can be minimized through careful experimental design, accurate measurements, and proper data analysis techniques.

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