A goodness-of-fit test for any statistical distribution. The test relies on the fact that the value of the sample cumulative
density function is asymptotically normally distributed.
To apply the Kolmogorov-Smirnov test, calculate the cumulative frequency (normalized by the sample size) of the observations as a function of class. Then calculate the
cumulative frequency for a true distribution (most commonly, the normal
distribution). Find the greatest discrepancy between the observed and expected
cumulative frequencies, which is called the "-statistic." Compare this against the critical -statistic for that sample size. If the calculated -statistic is greater than the critical one, then reject the
null hypothesis that the distribution is of the
expected form. The test is an R-estimate.