|Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more.|
|See also: normal distribution, chi-square test, Kolmogorov-Smirnov test, Shapiro-Wilk Test|
Test for Normality
The test for normality is a commonly needed procedure, since many of the statistical procedures are assumed to be applied to normally distributed data. In general, the test for normality can be achieved by applying a goodness-of-fit method (i.e. chi-square test, or Kolmogorov-Smirnov test). These two tests, however, do not perform well (the power of these tests is not too high). Therefore some other tests have been developed, which have various advantages but also some drawbacks: the power of the Shapiro-Wilk test is good, but the calculation procedure is rather cumbersome. A comparison of various tests for normality is given in the book of D'Agostino and M.A. Stephens.
The following table provides a survey on the most common tests for comparing distributions. All but the Shapiro-Wilk test can also be used to test for distributions other than the normal distribution.
Last Update: 2012-10-08