Regression model

Lilliefors Test for Normality

The Lilliefors test is a goodness-of-fit test that checks whether a continuous sample comes from a normal (or exponential) distribution when the mean and variance are unknown and estimated from the data. Introduced by Hubert W. Lilliefors in 1967, it adjusts the critical values of the Kolmogorov-Smirnov test so that they remain valid once the distribution's parameters are estimated rather than known in advance.

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Sources

  1. Lilliefors, H. W. (1967). On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown. Journal of the American Statistical Association, 62(318), 399-402. DOI: 10.1080/01621459.1967.10482916
  2. Dallal, G. E., & Wilkinson, L. (1986). An Analytic Approximation to the Distribution of Lilliefors's Test Statistic for Normality. The American Statistician, 40(4), 294-296. DOI: 10.1080/00031305.1986.10475419

Related methods

Referenced by

ScholarGateLilliefors Test (Lilliefors Test for Normality with Mean and Variance Unknown). Retrieved 2026-06-04 from https://scholargate.app/en/statistics/lilliefors-test