Gibrat's Law: The Central Limit Theorem's Forgotten Twin

Hiding in the shadow of the central limit theorm is a lesser-know, but still fascinating aspect of statistics. Read this post to what this is and how we can use it.

Generating Normal Random Variables - Part 1: Inverse Transform Sampling

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.
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