Uncertainty Analysis: Understanding Errors in Quantity Measurements

In summary, the conversation discusses three types of errors in uncertainty analysis: reading error, standard deviation, and equipment accuracy. The question is which error should be used for reporting the final quantity. Some references suggest propagating all three errors, while others suggest ignoring the smaller ones and using the maximum error. The standard way for error analysis depends on the significance of each error and the measurement equation.
  • #1
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.
 
Physics news on Phys.org
  • #2
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.
 
  • #3
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.
 
  • #4
what is your measurement equation?
 

1. What is uncertainty analysis?

Uncertainty analysis is a method used to evaluate the level of uncertainty or error in a measurement or quantity. It involves identifying and quantifying all potential sources of error and their impact on the final measurement result.

2. Why is uncertainty analysis important?

Uncertainty analysis is important because it helps us understand the accuracy and reliability of our measurement results. By identifying and evaluating potential sources of error, we can minimize their impact and improve the overall quality of our data.

3. How is uncertainty expressed?

Uncertainty is typically expressed as a range of values, often using a standard deviation or confidence interval, to represent the potential error in a measurement. This allows us to account for all sources of error and provide a more accurate and precise measurement result.

4. What are the sources of uncertainty in measurement?

The sources of uncertainty in measurement can vary depending on the type of measurement and the equipment used. Some common sources include instrument error, human error, environmental conditions, and sample variability. It is important to identify and evaluate all potential sources of uncertainty in order to accurately assess the overall error in a measurement.

5. How can uncertainty be reduced?

Uncertainty can be reduced by using more precise and accurate equipment, following standardized procedures, and minimizing sources of error wherever possible. Regular calibration and verification of measurement devices can also help reduce uncertainty and improve the reliability of measurement results.

Similar threads

  • Other Physics Topics
Replies
1
Views
2K
  • Introductory Physics Homework Help
Replies
15
Views
1K
Replies
7
Views
609
  • Other Physics Topics
Replies
13
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
21
Views
2K
  • Other Physics Topics
Replies
3
Views
6K
Replies
1
Views
1K
Replies
5
Views
1K
  • Other Physics Topics
Replies
4
Views
2K
Back
Top