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Be careful how you average – a retail example
- simulate 14y agoStanford'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/ 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-Uncertainty/dp/0471381977 http://www.amazon.com/Flaw-Averages-Underestimate-Risk-Uncer...
- Evbn 14y agoCool book, but sad that the public on average seems hopeless at understanding that variance exists.
- jbeda 14y agoI 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 14y agoTL;DR - use weighted averages. And there's a reason why people use median and mode. :)
- true_religion 14y agoI 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.
- Evbn 14y agoYeah, personalized analysis beats treating the population as uniform.