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 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 float, while `dof' should be an integer. The null hypothesis is roughly that `t-statistic' is zero; you must specify your 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 parameter is :positive, H1 is that `t-statistic' is positive, and similarly for :negative. This implementation follows Numerical Recipes in C, section 6.3.