The Kolmogorov-Smirnov Goodness-of-Fit Test

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Given a sample of size n from a continuous distribution function, F,
the Smirnov test tests the null hypothesis that F=F0,
where F0 is a given continuous distribution function.
The test statistic is Dn = supx|Fn(x)-F0(x)|, where Fn is the sample distribution function.
The distribution of Dn is independent of F0 when F0 is the true distribution function. 
      Enter n and the cutoff point.

    Sample size n: 
          d-value: 





   P(Dn <= d) :
For example, P(D100 <= .1) = .74731. For nd<=20, the exact probabilities for Dn are calculated.
As n tends to infinity, the distribution of √n Dn approaches the Kolgomorov distribution.
If nd>20, the approximate probabilities are given using the Kolmogorov distribution.
The error is less than .001.