Thesis (M.A.)--Boston UniversityIn most of the non-parametric methods, only a few general assumptions are made concerning the underlying distribution of the population from which a certain sample is drawn. One of the most frequent of these assumptions is that of continuity, i.e., that the population from which the sample is drawn possesses a continuous distribution, and, therefore, the probability of two or more equal observations is zero. Actually, however, due to limitation of measurement, experimental data are such that they must usually be regarded as coming from discontinuous distributions and equal observations will occur. When this is the case, one speaks of the occurrence of "tied" observations, or simply "ties", in the data. [TRUNCATED]
In this paper are discussed the dif£erent solutions that various statisticians have suggested in treating tied observations when applying the following non-parametric tests: (1) the sign test, (2) the Wilcoxon (Mann-Whitney) test, (3) the Wald-Wolfowitz Runs test, (4) The Moses test, (5) the Kruskal-Wallis test, (6) Kendall's rank correlation coefficient test, and {7) Kendall's coefficient of concordance test. It is found that most of the statisticians recommend the mid-rank method of treating ties
