In this paper an elementary exploration is given of some of the features of Q-discrimination analysis, an adaptation by Johnson of Atkin's Q-analysis for use in clustering work. The method is summarised. It is shown how the performance of the method varies considerably, depending upon whether the data involved are integer or noninteger, over a given range of values, and on whether they are ordinal or interval. An ambiguity over the criteria for determining discrimination levels is also considered.
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