Test for the mean of a Gaussian
Student t-test for a Gaussian mean
This function assumes the input signal to be Gaussian, i.e. to have a normal probability distribution function, and performs a Student t-based significance test to test the difference between the given and the actual mean value of the distribution.
The results of "Test for the mean of a Gaussian" will appear in the message window.
Input parameters are
- varknown, which denotes whether the variance is
- "known" (0) or
- "unknown" (1).
- mean, which is the mean value of the signal assumed for
the test and
- var, which is the variance, if it is known (otherwise
this parameter is ignored).
"Test for the mean of a Gaussian" returns two parameters:
- t, the t-value (see Student t-test -- Test for different means), and
- the significance signif, i.e. the probability [0..1] for x to have the test mean value by chance. Small values indicate a significant difference from mean.
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 variance of a Gaussian, Wilcoxon test
Hollander/Wolfe , Lehmann