“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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3-D-Printed Time Series Plates
After seeing a 1950s physical visualization, I wondered if I could follow a similar process using modern techniques.
If We All Left to “Go Back Where We Came From”
Imagine that those with immigrants in their family tree left the country. Almost everyone, basically.