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The Intersection Of Multiple Averages Is The Empty Set

Adi Gaskell argues that we shouldn’t get too wrapped up in “average” behaviors:

I’ve written extensively about the tremendous potential for big data in healthcare to drive enormous changes in how we keep people healthy for longer. It goes without saying however that all data is not created equal, and just having a large sample is not always sufficient to get the best insights.

If we needed reminding, a reminder comes via a recent¬†study¬†from the University of California, Berkeley. It suggests that things like emotion, behavior, and physiology vary hugely between individuals, therefore having an average over a large dataset can still produce a ‘norm’ that is wide of the mark for individuals.

“If you want to know what individuals feel or how they become sick, you have to conduct research on individuals, not on groups,” the researchers say. “Diseases, mental disorders, emotions, and behaviors are expressed within individual people, over time. A snapshot of many people at one moment in time can’t capture these phenomena.”

Variance is important.