added bug fixes to ProbDistOfSumOfIndepRandVars, and added the new class ProbDistOfSumOfWeightedRandVars. Random forests appear to become arbitrarily more accurate in both of these experiment classos as training examples are added. 100,000 traninging instances gets the predicted probability of a positive classification (assuming 20 predictive numeric variables and 20 nonpredictive numeric variables (noise variables)), within 20% of the ground truth probability, in both experiments