“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]
Type I and II errors simplified
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Years You Have Left to Live, Probably
The individual data points of life are much less predictable than the average. Here’s a simulation that shows you how much time is left on the clock.
Chart of Cousins
For every family get-together I go to, it seems there are more kids running around. I know that they are related to me somehow, but what do I call them? Maybe this chart will help next time.