Finding the Relative Uncertainty for the Standard Error of the Mean

AI Thread Summary
The discussion centers on calculating the relative uncertainty of the Standard Error of the Mean (SEM). The formula for relative uncertainty is understood to be the standard deviation divided by the mean. Participants clarify that the relative uncertainty of SEM can be interpreted as SEM divided by the mean. The provided data includes means, standard deviations, and SEM values for various datasets. Ultimately, the consensus is that the relative uncertainty of the mean is indeed what is being sought.
Athenian
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Homework Statement
Get the relative uncertainty for the standard error of the mean. Afterward, multiply the value by the logarithm of the mean to obtain the uncertainty in the graph.
Relevant Equations
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While I will not be showing the graph here, I am trying to dissect what the question even means.

While I do understand that relative uncertainty can be found via the equation ##\frac{\sigma_A}{A}##, I do not understand how I can find the "relative uncertainty of SEM". Does anybody here have any ideas? Please refer to the table below for the data.

MEANSTANDARD DEVIATIONSTANDARD ERROR OF THE MEAN (SEM)
156.0083​
3.258683​
0.940701​
131.1333​
1.830218​
0.528338​
74.38333​
2.361368​
0.681668​
48.175​
2.965905​
0.856183​
31.275​
2.205005​
0.63653​
14.45833​
2.589299​
0.747466​

Thank you for reading through this short question!
 
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I think they want what I would have called the relative uncertainty of the mean, i.e. SEM divided by the mean.
 
Thanks for the response. In the end, I also interpreted the statement in the same manner.
 
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