Use of statistics in experiment

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Discussion Overview

The discussion revolves around the use of statistics in experimental measurements, specifically focusing on the estimation of random error in a single measurement using sample variance. Participants explore the implications of using multiple measurements to estimate the error associated with a single data point.

Discussion Character

  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions how the formula for random error can apply to a single measurement when it requires multiple data points, suggesting a potential inconsistency.
  • Another participant points out that the variance is not defined for a single measurement, emphasizing that a single data point cannot exhibit spread.
  • A different participant asserts that the equation should be used to predict a new single data point based on several existing data points, mentioning that the sample average should replace the population mean in the equation.
  • There is a suggestion that if the population mean is known, a different calculation method should be applied, specifically dividing by n instead of n-1.

Areas of Agreement / Disagreement

Participants express differing views on the application of statistical formulas to single measurements, with no consensus reached on the validity of the initial claim regarding random error estimation.

Contextual Notes

Limitations include the dependence on the definition of variance and the assumptions regarding the availability of multiple measurements versus a single measurement.

Astudious
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I have seen that "the best estimate for the random error σ(X) in a single measurement is given by

σ(X)2 ≈ 1/(n-1) * ∑((xi-μ)2) where the sum is over all i"

I have two questions about this: firstly, how can this pertain to a "single measurement" if it requires the data from multiple measurements (x1, x2, x3, ... xi)? Secondly, this seems to correspond to the sample variance - wouldn't it be a more accurate estimate of the value of X's random error to convert to the variance of the population of X as a whole?
 
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Astudious said:
I have seen that "the best estimate for the random error σ(X) in a single measurement is given by

Where did you see this?

If you look at your equation and plug in n = 1, is the variance defined?
 
I don't see where it says anything about the variance determined from a single measurement in that article. Where did you see that?
 
If you want to use several data points that you already have to predict what will happen for a new or unknown single data point, that is the equation you should use.

PS, The correct equation uses the sample average of the existing data in place of μ. If some how you know μ, you can use it, but divide by n rather than n-1.
 

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