Student's distribution is much like the Gaussian distribution except with
heavier tails, depending on the number of degrees of freedom, dof.' As dof'
goes to infinity, Student's distribution approaches the Gaussian. This function
computes the significance of t-statistic.' Values range from 0.0 to 1.0: small<br> values suggest that the null hypothesis---that t-statistic' is drawn from a t
distribution---should be rejected. The t-statistic' parameter should be a<br> float, while dof' should be an integer.
The null hypothesis is roughly that t-statistic' is zero; you must specify your<br> alternative hypothesis (H1) via the tails' parameter, which must be :both,
:positive or :negative. The first corresponds to a two-tailed test: H1 is that t-statistic' is not zero, but you are not specifying a direction. If the<br> parameter is :positive, H1 is that t-statistic' is positive, and similarly for
:negative.
This implementation follows Numerical Recipes in C, section 6.3.