Why context is as important as the data itself
▻http://flowingdata.com/2010/05/21/why-context-is-as-important-as-the-data-itself
Why context is as important as the data itself
May 21, 2010 to Design, Statistics by Nathan Yau
John Allen Paulos, a math professor at Temple University, explains, in the New York Times, the importance of the before and after of when you get that data blobby thing in your hands.
The problem isn’t with statistical tests themselves but with what we do before and after we run them. First, we count if we can, but counting depends a great deal on previous assumptions about categorization. Consider, for example, the number of homeless people in Philadelphia, or the number of battered women in Atlanta, or the number of suicides in Denver. Is someone homeless if he’s unemployed and living with his brother’s family temporarily? Do we require that a women self-identify as battered to count her as such? If a person starts drinking day in and day out after a cancer diagnosis and dies from acute cirrhosis, did he kill himself?
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