Test for non-normal-distributed data
Tests if a data sequence has a normal probability distribution
"Test for non-normal-distributed data" performs a Kolmogorov-Smirnov test to examine
the differences between the cumulative probability distribution
functions of the given signal and a Gaussian normal distribution.
The results of this test will appear in the message window giving the
- the maximum distance D (see Kolmogorov-Smirnov test)
- the significance signif, i.e. the probability [0..1] of
the signal having a normal distribution function by chance, where small values indicate significant differences from a normal distribution.
BDS test, Kolmogorov-Smirnov test,
Test for different histograms,
Test for different means, Test for different variances,
Test for non-white-noise,
Test for the mean of a Gaussian, Test for the variance of a Gaussian,
Hollander/Wolfe , Lehmann