The Smirnov test, also known as the Kolmogorov-Smirnov test, is a non-parametric statistical test used to determine if a sample comes from a specific distribution or to compare two samples. It assesses the maximum difference between the empirical distribution functions of the samples and the theoretical distribution, providing a way to evaluate goodness-of-fit. This test is particularly useful because it does not assume a specific distribution shape, making it versatile for various data types. It can be applied to both one-sample and two-sample scenarios, helping researchers understand the underlying distribution of their data without relying on parametric assumptions.