## Statistics #

In my previous life, back when I studied pure mathematics, I never really took statistics too seriously. In my head, I was taking the courses more just to remain employable than out of actual interest. Maybe it was more down to the presentation, which was very dry and almost entirely theoretical. But over the years the more I learn and the more I use it, especially Bayesian statistics and computation or simulation methods, the more I appreciate it as an elegant and efficient way to model to describe pretty much anything.

### Links and resources #

- The German tank problem, an interesting example of a simple but ingenious statistical idea being used to determine the production rate of German tanks in the second world war.
- A very interesting paper on a Bayesian alternative to traditional $t$-tests. Implemented in Python here.
- A new correlation coefficient that seems to address many of the shortcomings of many commonly used coefficients. Seems to be significantly more involved to compute though, but theoretically a very clean idea.
- Anscombe’s quartet of four very different datasets with the same correlation coefficient (and many other common descriptive statistics).