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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 / s2), |
which has the Student t distribution with ndf = N-1 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, s2 is the variance at position [index] [index] in the covariance matrix.
The returned probability p is the two-sided probability
p = 2 * studentQ (t, ndf) |
A low probability p means that the difference is significant.
© djmw 20040407