'Returns the confidence interval of the value, `effect` of the constraint.
This is currently only available for t and z tests.
Parameters
alpha : float, optional
The significance level for the confidence interval.
ie., The default `alpha` = .05 returns a 95% confidence interval.
Returns
ci : ndarray, (k_constraints, 2)
The array has the lower and the upper limit of the confidence
interval in the columns.'

def conf_int(self, obs=False, alpha=0.05):

    se = (self.se_obs if obs else self.se_mean)
    q = self.dist.ppf((1 - (alpha / 2.0)), *self.dist_args)
    lower = (self.predicted_mean - (q * se))
    upper = (self.predicted_mean + (q * se))
    return np.column_stack((lower, upper))
