Lilliefors test
Kolmogorov–Smirnov normality check when the mean and SD come from the sample.
When to use it
Use Lilliefors when you want a Kolmogorov–Smirnov check against a normal curve whose mean and standard deviation were estimated from the same column. That is the usual SPSS “K-S with Lilliefors significance correction”. Shapiro–Wilk is the other normality test Tensr runs by name.
Assumptions
At least four numeric values. The column cannot be constant. Tensr uses the Dallal–Wilkinson approximation for the p-value.
Running it in Tensr
Options
Prop
Type
Reading the output
The same 120 standard-normal draws. Lilliefors estimates the mean and variance from the sample.
Lilliefors (K–S) normality test for noise, n = 120. The primary result is not significant (p = .848). This is not large enough to treat the comparison this page is about as a reliable association. The result is non-significant: the data are still compatible with no effect. Metrics: D = 0.043; p-value = .848; N = 120.
Reporting (APA 7)
Lilliefors (K–S) normality test for noise, n = 120. This result is not significant (p = .848). Report the estimate with that p, and do not describe the pattern as a reliable effect.
Coming from SPSS
Explore → Normality plots with tests. The Kolmogorov–Smirnov row with a Lilliefors footnote is this check. The Shapiro–Wilk row is the other test.