The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large score sampling from the score distribution’s tail. Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. The analytic score distribution for geometry splitting/Russian roulette applied to a simple Monte Carlo problem and the analytic score distribution for the exponential transform applied to the same Monte Carlo problem are provided.