In this thesis two general problems concerning goodness-of- fit statistics based on the empirical distribution are considered. The first concerns the problem of adapting Kolmogorov-Smirnov type statistics to test for discrete populations. The significance points of the statistics are given and various power comparisons made. The second problem concerns testing for goodness-of-fit with censored data using the Cramér-von Mises type statistics. The small and large sample distributions are given and the tests are modified so that they can be used to test for the normal and the exponential distributions. The asymptotic theory is developed. Percentage points for the statistics are given and various small sample and large sample power studies are made, for the various cases.