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I have in my head a very simple concept, but it's difficult to search for. I feel like there must be a function for this in statistics, but I have no idea what to look for.

I have a 1 dimensional data set, a simple column of numbers. Let's say it's {1, 3, 6, 8, 5}. I want to find the absolute average difference, or step, between each data point. In this case the differences would be {2, 3, 2, 3}, so the average would be 2.5.

This post is after the same data, and I know I can generate a second set of data, then average it. But is there a statistical function that does this on the data set directly, without having to make an intermediate data set?

Thanks, Ian

Edit: Clarification regarding absolute steps

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  • $\begingroup$ I am not sure, just in case: it could be the moving average: en.wikipedia.org/wiki/Moving_average $\endgroup$ – iadvd Sep 11 '15 at 6:03
  • $\begingroup$ All you have to do is subtract the 1st term from the last, and then divide by one less than the number of terms. $(11-1)/(5-1)=2.5$. $\endgroup$ – Gerry Myerson Sep 11 '15 at 6:37
  • $\begingroup$ Nice approach @GerryMyerson. Unfortunately I neglected to say I am not interested in -ve values, I want absolute steps. I've updated the question. $\endgroup$ – Ian Sep 11 '15 at 22:55
  • $\begingroup$ Then I don't think there's any way to compute $(1/n)\sum_1^n|a_j-a_{j-1}|$ without computing the individual numbers $|a_j-a_{j-1}|$. $\endgroup$ – Gerry Myerson Sep 11 '15 at 23:11
  • $\begingroup$ It's not the answer I was looking for, but fair enough. If you post it as an answer @GerryMyerson, I'll mark it as such. $\endgroup$ – Ian Sep 13 '15 at 23:25
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I don't think there is any way to compute $${1\over n}\sum_{j=1}^n|a_j-a_{j-1}|$$ without computing the individual numbers $|a_j-a_{j-1}|$.

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