Clearly reviews the properties of important contemporary measures of association and correlation. Liebetrau devotes full chapters to measures for nominal, ordinal, and continuous (interval) data, paying special attention to the sampling distributions needed to determine levels of significance and confidence intervals. Valuable discussions also focus on the relationships between various measures, the sampling properties of their estimators and the comparative advantages and disadvantages of different approaches.

Sampling Distributions for Discrete Data

Under suitable assumptions, the multinomial distribution is the correct model for random samples from discrete populations. Consequently, this distribution and a special case, the binomial distribution, are fundamental to any discussion of measures of association for discrete data.

The Binomial and Multinomial Distributions

Suppose the members of a population are partitioned into k categories Cl, …, Ck on the basis of ...

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