“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]
Become a member.
Learn to visualize your data.
From beginner to advanced.
What you get
I wanted to see how daily patterns emerge at the individual level and how a person’s entire day plays out. So I simulated 1,000 of them.
For various occupations, the difference between the person who makes the most and the one who makes the least can be significant.
Most of the major pizza chains are within a 5-mile radius of where I live, so I have my pick, …
The ever so popular Walmart growth map gets an update, and yes, it still looks like a wildfire. Sam’s Club follows soon after, although not nearly as vigorously.