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 "D-statistic."
Compare this against the critical D-statistic for
that sample size. If the calculated D-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.