Computing Errors when Data Sets are Given

In summary: One last question: We used an analog pressure gauge. So is the error in ##\Delta p=## least count of pressure gauge?
  • #1
Wannabe Physicist
17
3
Homework Statement
There are three relevant quantities, ##L,m,n##. I have been given: ##L = 7.056 \pm 0.005## cm. I also have the data set for measurements of ##m## taken as function of ##\Delta p##. I'd like to find the error in ##n##
Relevant Equations
##n = 1+\displaystyle\frac{\lambda p m}{2L\Delta p}##
This is for the lab report I have to submit. ##n## is the refractive index. ##L## is the length of a gas chamber and ##m## is the number of fringes passed as the pressure in the gas chamber changes by ##\Delta p##. We are already given the error in ##L##. I performed the experiment and obtained 16 observations. So I have the data sets ##m = \{m_i\}_{i=1}^{16}## and ##\Delta p = \{\Delta p_i\}_{i=1}^{16}##.

Now I am confused as to how to proceed to calculate the error in ##n##. I should obviously consider the error in ##L##. But how should I use the data sets to compute the error? Should the formula be
$$\frac{\delta n}{n} = \frac{\delta L}{L} + \frac{\sigma_m}{\bar{m}\cdot \sqrt{16}} + \frac{\sigma_{\Delta p}}{\bar{\Delta p}\cdot \sqrt{16}}$$
where ##\bar{m}## and ##\sigma_m## are the mean and standard deviation for ##m## respectively and notations are similar for ##\Delta p##

A classmate of mine suggested using the least count of the pressure gauge (Pressure gauge was calibrated in Torr with least count = 10 Torr). But I don't know if this should be used.
 
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  • #2
##\sigma_m## and ##\sigma_{\Delta p}## are consequences of the choices made in conducting the experiment. Their ranges do not reflect any kind of uncertainty in the data.
It is unclear to me how m and ##{\Delta p}## were determined. I'll assume the pressure was changed until m changed then both recorded. That being so, there is no error in m.
The input from these data to the rest of the calculation consists of the slope of the straight line fit to ##{\Delta p}## plotted against m.
You know this must pass through the origin, but I am not sure offhand how one uses that... we can return to that if necessary.
So you need to find uncertainty in the slope given the data. Google for that.
 
  • #3
The readings were taken by reducing the pressure by regular intervals of 10 torr and counting the number of fringes that moved outwards within that interval.

I have already plotted the graph of ##m## vs. ##\Delta p## and can reasonably say my error in counting ##m## should be ##\pm 1##. I found this link which tells how to find the uncertainty of slope: http://spiff.rit.edu/classes/phys311/workshops/w2c/slope_uncert.html

With this help, the slope of my plot is ##0.1 \pm 0.0135## Torr##^{-1}##

So now I think the error formula should be
$$\frac{\delta n}{n} = \frac{\delta L}{L} + \frac{0.0135}{0.1}$$
Is this formula correct?
 
  • #4
Wannabe Physicist said:
The readings were taken by reducing the pressure by regular intervals of 10 torr and counting the number of fringes that moved outwards within that interval.

I have already plotted the graph of ##m## vs. ##\Delta p## and can reasonably say my error in counting ##m## should be ##\pm 1##. I found this link which tells how to find the uncertainty of slope: http://spiff.rit.edu/classes/phys311/workshops/w2c/slope_uncert.html

With this help, the slope of my plot is ##0.1 \pm 0.0135## Torr##^{-1}##

So now I think the error formula should be
$$\frac{\delta n}{n} = \frac{\delta L}{L} + \frac{0.0135}{0.1}$$
Is this formula correct?
Looks reasonable to me.
 
  • #5
Okay. Thanks a lot. One last question: We used an analog pressure gauge. So is the error in ##\Delta p=## least count of pressure gauge? Or should I take no error in ##\Delta p##?

For my post #3 I assumed no error
 
  • #6
Wannabe Physicist said:
Okay. Thanks a lot. One last question: We used an analog pressure gauge. So is the error in ##\Delta p=## least count of pressure gauge? Or should I take no error in ##\Delta p##?

For my post #3 I assumed no error
Are you saying the reading is to the nearest 10Torr? If so, set the error to 5.
 
  • #7
Yes. Thanks a lot
 

1. What are computing errors when data sets are given?

Computing errors when data sets are given refer to the mistakes or inaccuracies that can occur during the process of analyzing and interpreting data. These errors can be caused by a variety of factors, such as faulty data collection methods, human error, or technical issues.

2. How do computing errors affect data analysis?

Computing errors can significantly impact the accuracy and reliability of data analysis. They can lead to incorrect conclusions and decisions based on faulty data, which can have serious consequences in scientific research and other fields.

3. What are some common types of computing errors?

Some common types of computing errors include measurement errors, transcription errors, calculation errors, and data entry errors. These errors can occur at any stage of the data analysis process and can be caused by various factors.

4. How can computing errors be prevented?

To prevent computing errors, it is essential to have a thorough understanding of the data and the methods used for data collection and analysis. It is also crucial to have proper quality control measures in place, such as double-checking data and using reliable software and tools.

5. What should be done if computing errors are discovered?

If computing errors are discovered, it is essential to identify the source of the error and determine its impact on the data analysis. If possible, the error should be corrected, and the data should be re-analyzed. In cases where the error cannot be corrected, it is crucial to acknowledge and address the error in the final report or publication.

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