Instrument Error or Standard Deviation

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SUMMARY

This discussion focuses on performing error analysis for distance measurements, specifically determining relative error. The two primary methods discussed are using instrument uncertainty divided by the mean measurement (0.005m / mean measurement) and calculating absolute error through standard deviation using the formula σx=sx/(N1/2). It is established that using the larger of the two values is a common practice to account for potential errors. Additionally, calculating error directly from a dataset is recommended, utilizing the standard deviation formula with n-1 for accuracy.

PREREQUISITES
  • Understanding of relative error and absolute error concepts
  • Familiarity with standard deviation calculations
  • Knowledge of Chauvenet's criterion for data analysis
  • Basic proficiency in statistical analysis of datasets
NEXT STEPS
  • Research the application of Chauvenet's criterion in error analysis
  • Learn about calculating standard deviation using n-1 for sample data
  • Explore methods for direct error calculation from datasets
  • Investigate the implications of random vs. systematic errors in measurements
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Researchers, data analysts, and engineers involved in precision measurement and error analysis in scientific experiments.

no_face
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I had a question about how to properly perform error analysis on a series of distance measurements. I need to find the relative error in the distance. I was wondering, should I use the instrument uncertainty divided by the measurement (in this case, it would be 0.005m / (mean measurement)). Or, should I be using the formula that relates absolute error to standard deviation: σx=sx/(N1/2), then use this value to find relative error. Or, should I use whichever one is larger to account for the largest possible error?
 
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no_face said:
I had a question about how to properly perform error analysis on a series of distance measurements. I need to find the relative error in the distance. I was wondering, should I use the instrument uncertainty divided by the measurement (in this case, it would be 0.005m / (mean measurement)). Or, should I be using the formula that relates absolute error to standard deviation: σx=sx/(N1/2), then use this value to find relative error. Or, should I use whichever one is larger to account for the largest possible error?

Both are reasonable ball park estimates, and using the larger one is a common approach. There are subtleties regarding random and systematic errors which prevent either from being rigorous.
 
no_face said:
I had a question about how to properly perform error analysis on a series of distance measurements. I need to find the relative error in the distance. I was wondering, should I use the instrument uncertainty divided by the measurement (in this case, it would be 0.005m / (mean measurement)). Or, should I be using the formula that relates absolute error to standard deviation: σx=sx/(N1/2), then use this value to find relative error. Or, should I use whichever one is larger to account for the largest possible error?

If you have a data set I always recommend calculating error from it directly. You should find ##\alpha = \frac{σ_{n-1}}{{n^{1/2}}}##, remember to calculate the standard deviation as n-1, you lose a degree of freedom when working from the set. You can then analyze the data, apply Chauvenet's criterion, relative error, etc.
 

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