Finding error margin when one term is 0

In summary, the conversation discusses finding error percent in measured values and how it applies to an experiment about conservation of momentum and energy in an elastic collision. It also brings up the concept of root mean square error for computing error in final results.
  • #1
Chen
977
1
In our labs we often need to find the error percent between the expected value and the measured value. So if we expected to get a value of 9.8 m/s2 for g but got 9.9 m/s2 instead, we say that the error was (9.9 - 9.8)/9.8 % = 1.02%. But what happens if we expect a value of 0 for something, and measure 1cm instead?
 
Mathematics news on Phys.org
  • #2
Chen,

Are you really measuring something whose correct length is zero, or are you measuring two non-zero lengths that are supposed to be the same?
 
  • #3
It is an experiment about conservation of momentum and energy in an elastic collision. The original momentum in the Y axis is 0, so the total momentum in that axis after the collision must also equal 0. Dropping the units for a second, let's say that the momentum in the Y axis after collision is (6) + (-5.9) = 0.1. What's the error percent then? :smile:
 
  • #4
Undefined, that's what.
 
  • #5
Chen said:
It is an experiment about conservation of momentum and energy in an elastic collision. The original momentum in the Y axis is 0, so the total momentum in that axis after the collision must also equal 0. Dropping the units for a second, let's say that the momentum in the Y axis after collision is (6) + (-5.9) = 0.1. What's the error percent then? :smile:

How about .1/6 or .1/5.9 depending on whether 6 or 5.9 is more likely to be correct?
 
  • #6
Compute the error in each of your measured values (.6) (.59) Then compute either a room mean square error or just use the Max error for the error of the final computation. It may be that your error will be larger then your final result. In which case you can claim to have a correct measuement within your error.

[tex]\mbox{rms} = \sqrt {{ \Delta x_1 }^2 + {\Delta x_2}^2}[/tex]
 

1. How do you calculate error margin when one term is 0?

When one term is 0, the error margin can be calculated by dividing the absolute error by the exact value of the term. This will give the relative error, which can then be converted into a percentage by multiplying by 100.

2. Why is it important to find the error margin when one term is 0?

Finding the error margin is important because it allows us to understand the accuracy and precision of our measurements or calculations. When one term is 0, it can significantly affect the overall result, so determining the error margin helps to account for this and provide a more accurate representation of the data.

3. Can the error margin be negative when one term is 0?

No, the error margin cannot be negative when one term is 0. This is because the absolute error is always a positive value, and when divided by 0, it will result in an undefined value. Therefore, the error margin will always be a positive value when one term is 0.

4. How does finding the error margin help in evaluating the reliability of data?

Finding the error margin helps in evaluating the reliability of data because it provides a measure of how much the data may deviate from the true value. A smaller error margin indicates a higher level of accuracy and precision, while a larger error margin suggests a lower level of reliability and potential for significant errors in the data.

5. Is the error margin the same as the uncertainty of a measurement?

No, the error margin and uncertainty of a measurement are not the same. The error margin is a measure of how much the data may deviate from the true value, while uncertainty refers to the range of values within which the true value is estimated to lie. The uncertainty of a measurement takes into account multiple sources of error, while the error margin typically focuses on a specific term or value in a calculation.

Similar threads

  • General Math
Replies
31
Views
1K
Replies
8
Views
3K
  • Classical Physics
Replies
18
Views
1K
  • Introductory Physics Homework Help
Replies
4
Views
511
  • Set Theory, Logic, Probability, Statistics
Replies
8
Views
2K
  • Engineering and Comp Sci Homework Help
Replies
20
Views
2K
Replies
1
Views
1K
  • Introductory Physics Homework Help
Replies
17
Views
1K
Replies
4
Views
2K
Back
Top