
Gets the level of significance for one mean from the selected Covariance object being different from a hypothesized mean.
This is the standard test on means when the variance is unknown. The test statistic is
t = (mean  μ) √(N / s^{2}), 
which has the Student t distribution with ndf = N1 degrees of freedom.
In the formulas above, mean is the element of the mean vector at position index, μ is the hypothesized mean, N is the number of observations, s^{2} is the variance at position [index][index] in the covariance matrix.
The returned probability p is the twosided probability
p = 2 * studentQ (t, ndf) 
A low probability p means that the difference is significant.
© djmw, April 7, 2004