Kstest python. kstest ¶ scipy. It is a non-parametric test which means you don't need to test any assumption related to the distribution of data. This tutorial explains what KS statistic is and how it is calculated, along with Python code. In this article, we will look at the non-parametric test which can be used to determine whether the shape of the two distributions is the same or not. kstest(rvs, cdf, args=(), N=20, alternative='two-sided', method='auto') [source] # Performs the (one-sample or two-sample) Kolmogorov-Smirnov test for goodness of fit. . Sep 12, 2025 · This comprehensive guide will walk you through implementing the KS test in Python, primarily leveraging the powerful statsmodels library and its integration with scipy. Note that kstest can also perform two-sample tests identical to those performed by ks_2samp. See Notes for a description of the available null and alternative hypotheses. kstest # scipy. In KS test, Null ks_2samp # ks_2samp(data1, data2, alternative='two-sided', method='auto', *, axis=0, nan_policy='propagate', keepdims=False) [source] # Performs the two-sample Kolmogorov-Smirnov test for goodness of fit. This performs a test of the distribution G (x) of an observed random variable against a given distribution F (x). statistic_location float Value of x corresponding with the KS statistic; i. statistic May 8, 2024 · In Python, the ks_2samp() function (from scipy) can be used for performing the two-sample Kolmogorov-Smirnov (KS) test. kstest function may also be used to check whether the data given follows Normal Distribution or not. Here is a practical intro for Python programmers with little background in statistics. You can either compare the statistic value given by python to the KS-test critical value table according to your sample size. e. Oct 14, 2016 · Let's say that we have two samples data1 and data2 with their respective weights weight1 and weight2 and that we want to calculate the Kolmogorov-Smirnov statistic between the two weighted samples. kstest(rvs, cdf, args= (), N=20, alternative='two-sided', mode='approx') [source] ¶ Perform the Kolmogorov-Smirnov test for goodness of fit. stats. It compares the observed versus the expected cumulative relative frequencies of the Normal Distribution. Jan 26, 2024 · A simple explanation of how to perform a Kolmogorov-Smirnov Test in Python, including several examples. This test compares the underlying continuous distributions F (x) and G (x) of two independent samples. Under the null hypothesis the two distributions are identical, G (x)=F (x). The Kolmogorov-Smirnov test uses the maximal absolute difference between the The KS test (Kolmogorov-Smirnov) is a practical tool to provide objective answers to such questions. Nov 23, 2024 · Learn how to efficiently conduct a two-sample Kolmogorov-Smirnov test in Python using Scipy's built-in functions. Parameters Feb 7, 2022 · Original by Chris Yang on Unsplash Imagine you have two sets of readings from a sensor, and you want to know if they come from the same kind of machine. Mar 23, 2025 · In Python, the KS test can be easily implemented, providing a powerful tool for data analysts and statisticians to make inferences about data distributions. The alternative hypothesis can Mar 1, 2024 · Output: KS Test is a very powerful way to automatically differentiate samples from a different distribution. Jul 17, 2023 · The KS Test is accessible and simple to apply with Python's practical implementation, offering solid statistical insights. When statistic value is higher than the critical value, the two distributions are different. For example, when two samples are drawn from the same distribution, we expect the data to be consistent with the null hypothesis most of the time. How do you compare those distributions? The quick answer is: you can use the 2 sample Kolmogorov-Smirnov (KS) test, and this article will walk you through this process. 2), one-dimensional probability distributions that can be used to compare a sample with a reference probability distribution (one-sample K–S I've read through existing posts about this module (and the Scipy docs), but it's still not clear to me how to use Scipy's kstest module to do a goodness-of-fit test when you have a data set and a KS test statistic, either D+, D-, or D (the maximum of the two) pvalue float One-tailed or two-tailed p-value. Jul 11, 2025 · The Kolmogorov-Smirnov (KS) test is a non-parametric method for comparing distributions, essential for various applications in diverse fields. This blog post will explore the fundamental concepts of the KS test, how to use it in Python, common practices, and best practices. The Kolmogorov-Smirnov (KS) test is a nonparametric test that assesses if two samples come from the same distribution. The KS Test can be your go-to tool for thorough statistical testing, whether you're a data scientist attempting to verify the performance of a machine learning model, a financial analyst checking assumptions about your data May 11, 2014 · scipy. Comparing Distributions Often in statistics we need to understand if a scipy. , the distance between the empirical distribution function and the hypothesized cumulative distribution function is measured at this observation. What is KS Statistic? KS test stands for Kolmogorov–Smirnov test which compares the two cumulative distributions and returns the maximum difference between them. The one-sample test compares the underlying distribution F (x) of a sample against a given distribution G (x). The two-sample test compares the underlying distributions of two independent samples In statistics, the Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous (or discontinuous, see Section 2. 4ib tb3me 1e9x l5ifq8 dgp a6kh 5ld oddngy ozbv luccoya