Normality tests

Lilliefors test

In statistics, the Lilliefors test is a normality test based on the Kolmogorov–Smirnov test. It is used to test the null hypothesis that data come from a normally distributed population, when the null hypothesis does not specify which normal distribution; i.e., it does not specify the expected value and variance of the distribution. It is named after Hubert Lilliefors, professor of statistics at George Washington University. A variant of the test can be used to test the null hypothesis that data come from an exponentially distributed population, when the null hypothesis does not specify which exponential distribution. (Wikipedia).

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Related pages

Variance | Jarque–Bera test | Kolmogorov–Smirnov test | Empirical distribution function | Expected value | Monte Carlo method | R (programming language) | Statistics | Probability distribution | Normality test | Cumulative distribution function | Normal distribution | Exponential distribution | Statistical significance | Null hypothesis