“Type I” and “Type II” errors, names first given by Jerzy Neyman and Egon Pearson to describe rejecting a null hypothesis when it’s true and accepting one when it’s not, are too vague for stat newcomers (and in general). This is better. [via]
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See what we ate on an average day, for the past several decades.
We know spending changes when you have more money. Here’s by how much.
“Let the data speak” they say. But what happens when the data rambles on and on?
These are my picks for the best of 2015. As usual, they could easily appear in a different order on a different day, and there are projects not on the list that were also excellent.