How is Kolmogorov Smirnov statistic calculated?

How is Kolmogorov Smirnov statistic calculated?

General Steps

1. Create an EDF for your sample data (see Empirical Distribution Function for steps),
2. Specify a parent distribution (i.e. one that you want to compare your EDF to),
3. Graph the two distributions together.
4. Measure the greatest vertical distance between the two graphs.
5. Calculate the test statistic.

What does Kolmogorov-Smirnov test tell you?

The two sample Kolmogorov-Smirnov test is a nonparametric test that compares the cumulative distributions of two data sets(1,2). The KS test report the maximum difference between the two cumulative distributions, and calculates a P value from that and the sample sizes.

When to use Kolmogorov-Smirnov test for normality?

We can use this procedure to determine whether a sample comes from a population that is normally distributed (see Kolmogorov-Smirnov Test for Normality ). We now show how to modify the procedure to test whether a sample comes from an exponential distribution.

How to calculate DN in Kolmogorov Smirnov table?

The distribution of Dn can be calculated (see Kolmogorov Distribution ), but for our purposes now the important aspect of this distribution is the table of critical values. These can be found in the Kolmogorov-Smirnov Table. If Dn,α is the critical value from the table, then P(Dn ≤ Dn,α) = 1 – α.

Which is the best example of normality and symmetry?

Example 2: Using the KS test, determine whether the data in Example 1 of Graphical Tests for Normality and Symmetry is normally distributed. We follow the same procedure as in the previous example to obtain the results shown in Figure 4. Since the frequencies are all 1, this example might be a little easier to understand.

Which is a good fit for the normal distribution?

From the Kolmogorov-Smirnov Table we see that Since Dn = 0.0117 < 0.043007 = Dn,α, we conclude that the data is a good fit for the normal distribution. Example 2: Using the KS test, determine whether the data in Example 1 of Graphical Tests for Normality and Symmetry is normally distributed.