If you're familiar with the normal distribution and R programming, then it's likely you've learned to use pnorm to calculate p-values for analysis. However, the way a computer does this calculation is lesser known. Let's change that!

With the help of Monte Carlo simuilation and multiprocessing, we use Python to simulate poker hands and make an inference on bad beat jackpots... which live poker players won't stop talking about... ever.

Sparse data is common in statistical analysis; there are always going to be applications that have zero-inflated observations and finding the right tools to deal with it is important. Scipy sparse is a package that helps with this setting, but a more concrete exploration of when its better than more traditional approaches is warranted.

CSR is a technique that is used to perform matrix operations in sparse settings. However, even if you understand the big picture, it can be overwhelming to understand how it works. In this post, we explain how CSR works and provide a myriad of cases to flush out the CSR mechanism.