Kolmogorov-Smirnov Test

The Kolmogorov-Smirnov test is a statistical method used to compare the distributions of two datasets or to check if a single dataset matches a specific theoretical distribution. Essentially, it calculates the largest difference between the cumulative probabilities of the two distributions. If this difference is significant, it suggests that the datasets come from different populations or that the single dataset does not fit the expected model. This test is valuable in determining how well a model describes observed data, helping researchers draw valid conclusions from their analyses.