7.5.5 Testing a distribution with the KolmogorovSmirnov
distribution: kolmogorovt
The kolmogorovt command will use the Kolmogorov test to compare
sample data to a specified continuous distribution.
You need to provide kolmogorovt with either two lists of data
or a list of data followed by the name of a distribution with the
parameters.
The kolmogorovt command will return three values:

The D statistic, which is the maximum distance between the
cumulative distribution functions of the samples or the sample and
the given distribution.
 The K value, where K = D√n (for a single data set,
where n is the size of the data set) or K=D√n_{1} n_{2} /(n_{1} +
n_{2}) (when there are two data sets, with sizes n_{1} and n_{2}).
The K value will tend towards the KolmogorovSmirnov distribution
as the size of the data set goes to infinity.
 1  kolmogorovd(K), which will be close to 1 when the
distributions look like they match.
For example, if you enter
kolmogorovt(randvector(100,normald,0,1),normald(0,1))
you might get
["D=",0.112592987625,"K=",1.12592987625,"1kolmogorovd(K)=",0.158375510292]
and if you enter
kolmogorovt(randvector(100,normald,0,1),student(2))
you might get
["D=",0.0996114067923,"K=",0.996114067923,"1kolmogorovd(K)=",0.27418851907]