Inspired by a simple probability puzzle, I set out to determine the probability that a Poisson random variable is divisible by a given integer, before extending this result to calculate the distribution of the Poisson random variable modulo a divisor.
Principal component regression is a powerful technique from high-dimensional statistics. In this post I offer an alternative interpretation of the procedure as a way of generating PCA loadings for new covariates.
Don't waste your tin foil wrapping up your turkey when fashioning it into a hat is far more in need this Christmas. In this post I will reveal how advent calendar makers the world over, have been lying to you about. So launch your VPN and delete your cookies, we're about to take down Big Advent.
The normal distribution is one of the most important developments in the history of statistics. As well as its useful statistical properties, it is so well-loved for its omnipresence in the natural world, appearing in all sorts of contexts from epidemiology to quantum mechanics. This blog post, the first in a series of posts discussing how we can generate random normal variables, explores the theory behind and the implementation of inverse transform sampling.
Although the game of darts requires a tremendous amount of skill to be a good player, there is still a very large probabilistic element. In this post, we take undertake a stochastic analysis of the game in order to reach an optimum strategy for play depending on the typical accuarcy of your shots.
In this post, we take a simple coin-flipping puzzle and through scope-expansion and generalisation, turn it into a monster probability problem that we can be proud to have tackled. In it, we look at some clever techiques for calculating probabilities which are vital in any experienced statistian's toolbox.