How is uncertainty affected by absolute numbers?

Click For Summary

Discussion Overview

The discussion revolves around the calculation of uncertainty in the evaporation rate of water, particularly how absolute numbers influence this uncertainty. Participants explore methods for determining the uncertainty associated with measurements taken over a set time interval, including the implications of using constants in calculations.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant describes a method for measuring the evaporation rate and expresses confusion about how to calculate the uncertainty in this rate based on individual measurements and constants.
  • Another participant suggests that when dividing or multiplying by constants, the relative uncertainty remains unchanged, and Gaussian error propagation can be applied for short time intervals.
  • A different viewpoint proposes that for averaging rates, correlations between measurements must be considered, indicating that errors in individual measurements do not affect the overall average as they may offset each other.
  • One participant recommends using a least squares fit to determine the slope of a regression line for a more accurate estimate of the evaporation rate and its uncertainty, while cautioning against using the propagation of errors formula for this scenario.
  • A question is raised about whether the amount of evaporation at a given time depends on the total amount of water present at that time, introducing another layer of complexity to the discussion.

Areas of Agreement / Disagreement

Participants express differing views on the best methods for calculating uncertainty and the implications of measurement correlations. There is no consensus on a single approach, and the discussion remains unresolved regarding the optimal method for calculating uncertainty in evaporation rates.

Contextual Notes

Participants highlight the complexity of error propagation in measurements involving both absolute numbers and time intervals. There are unresolved assumptions regarding the influence of total water volume on evaporation rates and the applicability of different mathematical approaches.

legends784
Example:
Say I want to calculate the evaporation rate of water and so I record the mass of some amount of water every 30 seconds for 5 minutes. The uncertainty in the scale is inherently .0001g and so that would be the uncertainty in the mass of any individual measurement, but how would I calculate the uncertainty for what I am actually looking for which is a rate. I.e by finding the difference between each concurrent measurement, dividing it by 30seconds, then adding up each of the individual rates in g/s and calculating an average rate in mg/min.

I can't physically wrap my head around how the error transfers between each of these stages, especially because most of them involve dividing/multiplying by absolute numbers like 30seconds or 1000mg/g

All help is appreciated,
Alex
 
Physics news on Phys.org
If you divide or multiply by constants the relative uncertainty stays the same. For evaporation rates within 30 seconds Gaussian error propagation will work.
For the average, this doesn't work, as your measurements are correlated: If a measurement (apart from the first and last one) is off, it will increase one rate and decrease another. It won't influence the average at all.

You can calculate the average and its uncertainty just from the first and last measurement, similar to the 30s values. You'll get a better estimate if you make a trend line through all your data, however.
 
  • Like
Likes   Reactions: QuantumQuest and FactChecker
legends784 said:
what I am actually looking for which is a rate. I.e by finding the difference between each concurrent measurement, dividing it by 30seconds, then adding up each of the individual rates in g/s and calculating an average rate in mg/min.
A better approach would be to do a least squares fit to a regression line and obtain the slope. Most commercial packages will give you a standard error or a confidence interval for the slope.

There are ways to calculate what you suggest using the propagation of errors formula, but I would not recommend that approach.
 
  • Like
Likes   Reactions: QuantumQuest
Doesn't the amount that evaporates at stage ##t_0## also depend on the total amount of water present at ##t_0##?
 

Similar threads

  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 13 ·
Replies
13
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 8 ·
Replies
8
Views
3K