Be careful how you average – a retail example

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

by cpierson • 14 years ago

45 6 14 years ago

blog.custora.com

simulate• 14 years ago

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...

Evbn2• 14 years ago

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

jbeda• 14 years ago

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.

binarysolo• 14 years ago

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

true_religion• 14 years ago

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.

Evbn2• 14 years ago

Yeah, personalized analysis beats treating the population as uniform.

Be careful how you average – a retail example

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