Introduction

Introduction

If $X$ has a known distribution and we compute $Y = g(X)$, what is the distribution of $Y$? This question is everywhere: standardising features, log-transforming prices, generating random numbers, and normalizing flows that turn simple noise into realistic data. Densities don't transform like values — they must be corrected by how much $g$ stretches space.