Finally, assess whether the maximum discrepancy is large enough to be statistically significant, thus requiring rejection of the null hypothesis. This is where this test becomes more complicated than the Kolmogorov–Smirnov test. Since the hypothesized CDF has been moved closer to the data by estimation based on those data, the maximum discrepancy has been made smaller than it would have been if the null hypothesis had singled out just one normal distribution. Thus the "null distribution" of the test statistic, i.e. its probability distribution assuming the null hypothesis is true, is stochastically smaller than the Kolmogorov–Smirnov distribution. This is the Lilliefors distribution. To date, tables for this distribution have been computed only by Monte Carlo methods.