Test for non-normal-distributed data
Purpose
Description
Macro Synopsis
Modules
Related Functions
References
Purpose
Tests if a data sequence has a normal probability distribution
Description
"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
return parameters
- 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.
Macro Synopsis
NormalGaussTest(x,&D,&signif);
signal x;
float D,signif;
Modules
Statistics
Related Functions
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,
Wilcoxon test
References
Hollander/Wolfe [13], Lehmann [36]