I Uncertainty Analysis: Understanding Errors in Quantity Measurements

AI Thread Summary
Uncertainty analysis typically involves three types of errors: reading error, standard deviation from repeated measurements, and equipment accuracy. For reporting the final quantity as X_est +/- X_error, the standard approach is to propagate all three errors using the formula that combines them, such as the square root of the sum of their squares. However, some suggest that smaller errors can be ignored if they do not significantly impact the overall uncertainty, particularly if the largest error is much greater than the others. The choice of method may depend on the specific measurement context and the relative magnitudes of the errors involved. Understanding the measurement equation is crucial for determining the appropriate approach to error analysis.
Henryflycat
Hey,

I have a question about uncertainty analysis. So my university told me that, usually a quantity has 3 types of errors, reading error, standard deviation (which comes from some repeated measurements of that quantity), and equipment accuracy (which is usually stated on the equipment).

My question is, if I've got these 3 errors, to report the final quantity with X_est +/- X_error, which error should I use for X_error? Some references said I need to do a propagation of all these 3, like the square root of reading_error^2 + accuracy^2 + std_dev^2. Someone said we can ignore the smaller ones, just the take maximum of these 3 errors to be the final error X_error.

Which method is actually the standard way for error analysis? I'm pretty confused.

Thanks a lot.
 
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Henryflycat said:
Someone said we can ignore the smaller ones, just the take maximum of these 3 errors to be the final error X_error.

Ignore only if they do not significantly contribute to the overall uncertainty. It would not make a great deal of sense to include errors whose effect is less than the precision of the measure quantity.
 
Henryflycat said:
Someone said we can ignore the smaller ones, just the take maximum of these 3 errors to be the final error X_error.
You can only do this if the largest is much larger than the others.
 
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