What Justifies Using a Single SD for All Measurements in a Dataset?

In summary, the conversation discusses the use of standard deviation in measuring a quantity T, and how it can be used to find the width of the average in a dataset D. The question arises as to whether the SD found from the entire dataset can be used for each individual measurement. The answer lies in the assumption that all values in the dataset come from the same population with a constant SD.
  • #1
Niles
1,866
0
Hi

Ok, we all know that if a quantity T is measured N times, then all measurements have the same standard deviation (SD). Now, with this assumption one can derive the width of the average to get SD/sqrt(N).

I have often encountered a dataset D, where each measurement has been assigned no SD. Then one finds the SD for the whole dataset, and then the author uses SD/sqrt(N) to find the width of the average of D.

My question is: In these cases, then what justifies that SD found from the whole dataset D can be assumed to be valid for each single measurements, such that one can use SD/sqrt(N)?

I hope you understand.


Niles.
 
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  • #2
"In these cases, then what justifies that SD found from the whole dataset D can be assumed to be valid for each single measurements"

The assumption that all the values in the data set come from the same population - one having a constant standard deviation.
 
  • #3
Thanks, that makes sense.

Best wishes,
Niles.
 

1. What are uncertainties of averages?

Uncertainties of averages refer to the errors or variations that can occur in the calculated average of a set of data. It takes into account the individual uncertainties of each data point and provides a range within which the true average is likely to fall.

2. Why is it important to consider uncertainties of averages?

Considering uncertainties of averages is important because it provides a more accurate representation of the data. It takes into account the potential errors or variations in the data, giving a more realistic understanding of the true average.

3. How are uncertainties of averages calculated?

Uncertainties of averages are typically calculated using statistical methods, such as standard deviation or standard error. These calculations take into account the individual uncertainties of each data point and provide a range within which the true average is likely to fall.

4. What factors can contribute to uncertainties of averages?

There are several factors that can contribute to uncertainties of averages, including measurement errors, variations in the data, and the reliability of the measurement equipment. Additionally, the sample size and the distribution of the data can also affect the uncertainties of averages.

5. How can uncertainties of averages be reduced?

Uncertainties of averages can be reduced by increasing the sample size, using more precise measurement equipment, and minimizing errors and variations in the data. Additionally, using appropriate statistical methods to calculate uncertainties can also help to reduce the overall uncertainty in the average.

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