## 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]