# Kolmogorov-Smirnov Options (One-Sample Nonparametric Tests)

This dialog specifies which distributions should be tested and the parameters of the hypothesized distributions.

When certain parameters of the distribution have to be estimated from the
sample, the Kolmogorov-Smirnov test no longer applies. In these instances, the Lilliefors test
statistic can be used to estimate the *p*-value by using the Monte Carlo sampling for testing
normality with mean and variance unknown. The Lilliefors test applies to the three continuous
distributions (Normal, Exponential, and
Uniform). Note that the test does not apply if the underlying distribution is
discrete (Poisson). The test is only defined for one-sample inference when
the corresponding distribution parameters are not specified.

- Normal
- Use sample data uses the observed mean and standard deviation and provides options for selecting the existing Asymptotic test results, or use Lilliefors test based on the Monte Carlo sampling. Custom allows you to specify values.
- Uniform
- Use sample data uses the observed minimum and maximum and uses Lilliefors test based on the Monte Carlo sampling. Custom allows you to specify minimum and maximum values.
- Exponential
- Sample mean uses the observed mean and uses Lilliefors test based on the Monte Carlo sampling. Custom allows you to specify an observed mean value.
- Poisson
- Mean allows you to specify an observed mean value.