Contrarian view; the average is still a pretty fine measure, assuming one does
not over-interpret it, accompany it with a measure of variance and only apply
it a distributions where it intuitively makes sense (e.g. for distributions
like a gaussian curve, A-OK, for a bi-modal distribution with peaks symmetric
around zero probably not so much).
However the same caution should be used for alternative measures, beware of the
single number descriptions of complex data...
Regards
Sebastian
P.S.: Often it is not obvious from the beginning how a distribution is going to
look like, it seems dangerous to summarize to mean + variance at that stage
before actually looking at the data, however an easy trap to fall into
especially for sparse data.
> On Jul 10, 2022, at 18:20, Dave Taht via Starlink
> <[email protected]> wrote:
>
> This book is my weekend's reading. Excerpt:
>
> https://www.thestar.com/news/insight/2016/01/16/when-us-air-force-discovered-the-flaw-of-averages.html
> --
> FQ World Domination pending: https://blog.cerowrt.org/post/state_of_fq_codel/
> Dave Täht CEO, TekLibre, LLC
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