I need help in understanding how to test whether a statistic conforms to a known distribution so I can establish levels of significance. The statistic I'm using is one that's used to test similarity between two profiles (i.e., a variant of the sum of squared differences). This statistic can be calculated in two ways: (1) assuming uncorrelated profile elements and (2) with correlated profile elements. The uncorrelated version does follow the Chi-square distribution and tabled significances exist. No such table exists for the correlated version - which is the formula I'm using. So, I've got a large sample of individuals (N = 1108) who completed the survey. I can calculate the profile similarity coefficient comparing each respondent against every other respondent (the number of comparisons is about 1.22 million). I can generate the distribution of coefficient values. But, how do I test whether the distribution of scores follows the Chi-square distribution (or some other)? Then what do I do to generate a table of significances? Does someone know how to do this and can guide me through the process? Alternatively, can someone point me to references (for non-mathematicians) that explain how to do this kind of thing? Thanks. Edgar _____ Edgar F. Johns <EdgarJohns@obik.com> Obik, LLC 2906 River Meadow Circle Canton, MI 48188 Tel. 734.495.1292, Fax 734.495.1981 http://www.obik.com