Adjusted R-square
Analyse qualitative data. How to
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ANCOVA (Analyses of covariance)
ANOVA (Analyses of variance)
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Kolmogorov-Smirnov test
The Kolmogorov-Smirnov test is a commonly used test to check whether a variable is normally distributed. A statistically significant result indicates that the variable under investigation is not normally distributed.
The test is only useful for research with a small number of cases. From as early as 25 or more cases, the test almost always produces statistically significant results. It is therefore actually more surprising if there is no statistically significant result.
For small numbers (n <30) non-parametric tests are preferred. For larger numbers, the other tests are preferred. This preference is independent of the test result of the Kolmogorov-Smirnov test. Therefore the result of the Kolmogorov-Smirnov test has hardly any impact.
Better indicators for the normal distribution of a variable are skewness and kurtosis.
