Calculating measurement uncertainty

  • Context: Undergrad 
  • Thread starter Thread starter AbsoluteZer0
  • Start date Start date
  • Tags Tags
    Measurement Uncertainty
Click For Summary
SUMMARY

The discussion focuses on calculating measurement uncertainty, specifically how to determine the appropriate range of uncertainty (±.01, ±.02, ±.03) based on the measurement's decimal places. It clarifies that if the uncertainty is a statistical measure, it typically relates to standard deviation or standard error, while non-statistical uncertainty corresponds to a maximum error bound. The key takeaway is that for statistical measures, the uncertainty reflects a probabilistic proportion of errors, while for non-statistical measures, it is determined by the maximum error value.

PREREQUISITES
  • Understanding of standard deviation and standard error
  • Familiarity with maximum error bounds
  • Knowledge of statistical measures in uncertainty analysis
  • Basic principles of measurement and precision
NEXT STEPS
  • Research the differences between standard deviation and standard error in measurement contexts
  • Learn how to calculate maximum error bounds for various measurement types
  • Explore probabilistic models related to measurement uncertainty
  • Study best practices for reporting uncertainty in scientific measurements
USEFUL FOR

Researchers, quality control professionals, and anyone involved in precision measurement and uncertainty analysis will benefit from this discussion.

AbsoluteZer0
Messages
124
Reaction score
1
Hi,

I've been studying uncertainty in measurement. I'm not sure how to decide if the uncertainty of a given measurement should be ±.01 or ±.02 or ±.03, and so forth. I understand that the number of decimal places in the uncertainty calculation should correspond to the number of decimal places in the measurement, but I am not sure as to when I should decide whether the uncertainty contains a 1, 2, 3, and so forth.

Thanks,
 
Physics news on Phys.org
Hey AbsoluteZer0.

If it's a statistical measure of error, this usually corresponds to some kind of standard deviation or standard error (both refer to different things: one being a population measure typically and the other being a sample statistic typically), but if it's not statistical it may correspond a maximum error bound.

If it's the latter then typically you will figure out what the maximum error is and use that since all values will lie in-between +- that value.

If it's statistical then this is different because what happens usually in this case is that you have +- so many sigma contains a probabilistic proportion that a fraction of the errors according to some constraint will fall in that region and the rest won't.
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 21 ·
Replies
21
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 30 ·
2
Replies
30
Views
4K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 22 ·
Replies
22
Views
2K
  • · Replies 9 ·
Replies
9
Views
11K