I've calculated the mean difference of my (normally distributed) data set. The mean difference is defined as:(adsbygoogle = window.adsbygoogle || []).push({});

Now, I'm trying to calculate the "mean difference deviation" in order to generate a confidence interval for this quantity ( The average absolute difference of any two independent values in a data set"95% of the differences in the set are greater than ____"). My question is: can I generalize the standard deviation formula to calculate this? If we take the following concepts to be parallel:

Code (Text):

Mean <---------> Mean Difference

Single value <---------> Single Difference

... can I use the standard deviation equation to calculate the "mean difference deviation"? Namely turning this:

to this:Standard deviation calculation steps

1. Take the difference of the mean and each single value

2. Square each result and add up the resulting numbers

3. Divide by the total number of values

4. Take the square root of #3

I've looked up more direct ways to calculate this quantity, and all of them are contained in statistics articles that are way(1) over(2) my head(3); so much so that I can't even determine if its what I'm looking for, much less how to go about translating it in to code (and I haven't even touched on efficiency concerns).Proposed "mean difference deviation" calculation steps

1. Take the difference of the mean difference and each single difference

2. Square each result and add up the resulting numbers

3. Divide by the total number of differences

4. Take the square root of #3

Can anyone provide some insight? And if it turns out this can't be done, would anyone mind taking a crack at translating the derived equations in those articles in to English?

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# Can the standard deviation calculation be generalized for other statistics?

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