“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
10 Best Data Visualization Projects of 2015
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.
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.