How I Use ks.test in R to Perform a Kolmogorov-Smirnov Test

How I Use ks.test in R to Perform a Kolmogorov-Smirnov Test

Key points A KS test compares the distribution of a sample with a reference or two samples. It does not make assumptions about the underlying distribution. You can use the ks.test function in R to perform a KS test with different arguments and additional parameters. You can select a reference distribution for a KS test based on your understanding of the data or research question. Alternatively, you can use an empirical CDF from a different sample or perform a bootstrap resampling. To understand the result of a KS test, compare the p-value to your significance level. This will help you determine if the sample matches the reference distribution or if two samples have the same distribution. A Kolmogorov-Smirnov test (KS test) is a nonparametric test that compares a sample's cumulative distribution function (CDF) with a reference CDF or the CDFs of two samples.  The sentence can be simplified and split into several shorter coherent sentences as follows: It checks if a sample follows a speci…