

Be careful how you average – a retail example - cpierson
http://blog.custora.com/2012/08/be-careful-how-you-average-a-retail-example/

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simulate
Stanford's Sam Savage has written an excellent book on the topic of
disaggregating average data and mistakes made from using averages. Here's a
summary of the book on his website: <http://www.stanford.edu/~savage/flaw/>

and here's a link to his book, titled The Flaw of Averages:
[http://www.amazon.com/Flaw-Averages-Underestimate-Risk-
Uncer...](http://www.amazon.com/Flaw-Averages-Underestimate-Risk-
Uncertainty/dp/0471381977)

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Evbn
Cool book, but sad that the public on average seems hopeless at understanding
that variance exists.

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true_religion
I was never a math kingpin, but my last startup was stock market/trading
related so I got to brush shoulders with some brilliant analysts.

Their advice to me is "anytime you think you want to do a simple average,
you'd be better served by displaying a histogram of averages".

I think this completely applies here too since it would help you quickly see
if (a) the bulk of your customers are have a low repeat price and the average
is buoyed up by a few large purchases or (b) one customer orders a whole bunch
of tiny items at a low price dragging the averages down.

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jbeda
I see this type of thing come up all the time when monitoring complex
production systems.

Say you have 10 servers in each of 3 datacenters and you are looking at
request latency. Averaging all 30 servers is very different from averaging to
the datacenter and then averaging/alerting on a dc by dc basis.

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binarysolo
TL;DR - use weighted averages. And there's a reason why people use median and
mode. :)

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Evbn
Yeah, personalized analysis beats treating the population as uniform.

