How do you interpret a test statistic?
Interpreting test statistics The agreement between your calculated test statistic and the predicted values is described by the p-value. The smaller the p-value, the less likely your test statistic is to have occurred under the null hypothesis of the statistical test.
What is a high test statistic?
Test Statistics and P-Values The larger the test statistic, the smaller the p-value and the more likely you are to reject the null hypothesis. A p-value is an area in the tail of a distribution that tells you the odds of a result happening by chance.
What is the d statistic of the K-S test?
The D statistic is the absolute max distance (supremum) between the CDFs of the two samples. The closer this number is to 0 the more likely it is that the two samples were drawn from the same distribution. Check out the Wikipedia page for the k-s test.
When to use Kolmogorov’s d statistic in statistics?
Have you ever run a statistical test to determine whether data are normally distributed? If so, you have probably used Kolmogorov’s D statistic. Kolmogorov’s D statistic (also called the Kolmogorov-Smirnov statistic) enables you to test whether the empirical distribution of data is different than a reference distribution.
What does the d statistic mean in statistics?
The D statistic can help you determine whether a sample of data appears to be from the reference distribution. Throughout this article, the word “distribution” refers to the cumulative distribution. What is the Kolmogorov D statistic? The letter “D” stands for “distance.”
How to interpret p-value of K-S test?
The p-value returned by the k-s test has the same interpretation as other p-values. You reject the null hypothesis that the two samples were drawn from the same distribution if the p-value is less than your significance level. You can find tables online for the conversion of the D statistic into a p-value if you are interested in the procedure.