The article explores a test to see if a certain mathematical model fits real-world data well. The test is based on how likely different outcomes are, and uses a method called the Cramér-von Mises-type test. By using a technique called the bootstrap, researchers can accurately estimate how well the model fits the data, even with limited information. The study shows that this approach works well for small amounts of data, giving scientists a reliable way to check if their model accurately represents the real world.