Kolmogorov Smirnov Test Normality. Since dn 0 1874988 0 338 dn α we conclude that the data is a reasonably good fit with the normal distribution more precisely that there is no significant difference between the data and data which is normally distributed. Data were good and decent used in research is normally distributed data.
However it is almost routinely overlooked that such tests are robust against a violation of this assumption if sample sizes are reasonable say n 25. Given n ordered data points y1 y2 y n the ecdf is defined as e n n i n where n i is the number of points less than y i and. In statistics the kolmogorov smirnov test is a nonparametric test of the equality of continuous one dimensional probability distributions that can be used to compare a sample with a reference probability distribution or to compare two samples.
The kolmogorov smirnov test of normality.
It is named after andrey kolmogorov and nikolai smirnov. The following code shows how to perform a kolmogorov smirnov test on this sample of 100 data values to determine if it came from a normal distribution. The kolmogorov smirnov table shows that the critical value dn α d15 05 338. Data were good and decent used in research is normally distributed data.
