Contents
What is P value of Kolmogorov-Smirnov test?
STUDENT’S T-TEST The result, P-value, tells you how likely these samples comes from the exact same distribution. When obtained, the P-Value can be compared with a threshold call statistical significance (e.g. . 05), if the P-Value is smaller, we can reject the null hypotheses.
Why is Kolmogorov-Smirnov test?
The Kolmogorov-Smirnov test (Chakravart, Laha, and Roy, 1967) is used to decide if a sample comes from a population with a specific distribution. An attractive feature of this test is that the distribution of the K-S test statistic itself does not depend on the underlying cumulative distribution function being tested.
When do you use the Kolmogorov Smirnov test?
Statistics – Kolmogorov Smirnov Test. This test is used in situations where a comparison has to be made between an observed sample distribution and theoretical distribution. K-S One Sample Test. This test is used as a test of goodness of fit and is ideal when the size of the sample is small.
When to use K’s table in Smirnov test?
The critical value of D for samples where and is ≤ 40, the K-S table for two sample case is used. When and/or > 40 then the K-S table for large samples of two sample test should be used. The null hypothesis is accepted if the calculated value is less than the table value and vice-versa.
When to use K-S two sample test?
K-S Two Sample Test. When instead of one, there are two independent samples then K-S two sample test can be used to test the agreement between two cumulative distributions. The null hypothesis states that there is no difference between the two distributions. The D-statistic is calculated in the same manner as the K-S One Sample Test.
How to calculate the KINV of the Kolmogorov distribution?
where c(α) = the inverse of the Kolmogorov distribution at α, which can be calculated in Excel as Dm,n,α = KINV (α)*SQRT ((m+n)/ (m*n)) where KINV is defined in Kolmogorov Distribution. The values of c(α) are also the numerators of the last entries in the Kolmogorov-Smirnov Table.