“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
Projects by Nathan Yau See All →
How Much Alcohol Americans Drink
Most people have one or two drinks on average, but some consume much more.
Who is Older and Younger than You
Here’s a chart to show you how long you have until you start to feel your age.
Data, R, and a 3-D Printer
We almost always look at data through a screen. It’s quick and good for exploration. So is there value in making data physical? I played around with a 3-D printer to find out.