Average Value Uncertainty: How to Compute?

In summary, average value uncertainty refers to the uncertainty in the calculated average value of a set of data. To compute this uncertainty, one must first calculate the standard deviation of the data set. The average value uncertainty is then equal to the standard deviation divided by the square root of the number of data points. This measure of uncertainty is important in understanding the reliability of the calculated average and can help in making decisions based on the data.
  • #1
DoobleD
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I have a set of values I got from measurements, and each of these value has an uncertainty associated to it.

I compute the average of my values. How can I average the uncertainty associated to my average value ? Do I simply take the average of all uncertainties ?
 
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  • #2
No. This way you do injustice to accurate measurements and you let bad measurements have too much weight.
There are simple rules for this. The average isn't the best estimate: that is the http://www.colorado.edu/physics/phys2150/phys2150_sp14/phys2150_lec4.pdf.
 
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Likes DrClaude and DoobleD
  • #3
BvU said:
No. This way you do injustice to accurate measurements and you let bad measurements have too much weight.
There are simple rules for this. The average isn't the best estimate: that is the http://www.colorado.edu/physics/phys2150/phys2150_sp14/phys2150_lec4.pdf.

Thank you ! I have just read somewhere that indeed this is more precise and used more often in practice when we have a large set of values for a measurement.
 
  • #4
BvU said:
No. This way you do injustice to accurate measurements and you let bad measurements have too much weight.
There are simple rules for this. The average isn't the best estimate: that is the http://www.colorado.edu/physics/phys2150/phys2150_sp14/phys2150_lec4.pdf.
Loved the Dilbert comic in that link.
 

FAQ: Average Value Uncertainty: How to Compute?

1. What is average value uncertainty?

Average value uncertainty is a measure of the amount of uncertainty in a set of data or measurements. It represents the range of values that the true value of a quantity could fall within, taking into account all sources of error and variability in the data.

2. Why is it important to compute average value uncertainty?

Computing average value uncertainty allows scientists to understand the reliability and accuracy of their data. It also helps to determine the precision of measurements and identify any sources of error that may be present.

3. How is average value uncertainty calculated?

The formula for calculating average value uncertainty is: uncertainty = (maximum value - minimum value) / 2. This takes into account the range of values in the data set and divides it by two to represent the uncertainty in the middle of the range.

4. What factors can contribute to average value uncertainty?

There are several factors that can contribute to average value uncertainty, including instrumental error, human error, and natural variability in the data. It is important to identify and minimize these sources of uncertainty to improve the accuracy and reliability of data.

5. How can average value uncertainty be reduced?

To reduce average value uncertainty, scientists can use more precise instruments, improve measurement techniques, and increase the number of measurements taken. It is also important to identify and control any sources of error and variability in the data.

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