Test for the variance of a Gaussian
Variance Chi-square test
"Test for the variance of a Gaussian" assumes the input signal to be Gaussian, i.e. to
have a normal probability distribution function and performs a
Chi-square-based significance test
(Test for different histograms) to test the differences between the
test variance and the actual variance of the distribution.
The test results are output in the message window.
"Test for the variance of a Gaussian" takes one parameter which is the
and returns two parameters
- chisq, which is the value, and
- signif, which is the significance, i.e. the probability
[0..1] for x to have the given test variance by chance. Small values indicate a significant difference from var.
BDS test, Kolmogorov-Smirnov test,
Test for different histograms,
Test for different means, Test for different variances,
Test for non-normal-distributed data,
Test for non-white-noise,
Test for the mean of a Gaussian, Wilcoxon test
Hollander/Wolfe , Lehmann