“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]
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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.
There are many exercise apps that allow you to keep track of your running, riding, and other activities. Record speed, …
I call myself a statistician, because, well, I’m a statistics graduate student. However, the most important things I’ve learned are less formal, but have proven extremely useful when working/playing with data.
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.