There are four procedures to present the implications of a correlation in terms of our ability to use the correlations to make successful predictions:Binomial effect size display (dichotomous)This illustrates the practical consequences of using correlations to make decisions. It can show how many successful and unsuccessful predictions can be made on the basis of a correlation. It uses the following formula:Binomial effect size display can be used to translate a validity correlation into an intuitive framework. However, it frames the situation in terms of an ‘equal proportions’ situation. Taylor-Russell tables (dichotomous)These tables inform selection decisions and provide a probability that a prediction will result in a successful performance on a criterion. The size of the validity coefficient (1), selection proportion (2) and the base rate (3) are required for the tables. Utility analysisThis frames validity in terms of a cost-benefit analysis of test use. Analysis of test sensitivity and test specificityA test is evaluated in terms of its ability to produce correct identifications of a categorical difference. This is useful for tests that are designed to detect a categorical difference.Validity correlations can be evaluated in the context of a particular area of research or application.A nomological network refers to the interconnections between a construct and other related construct. There are several methods to evaluate the degree to which measures show convergent and discriminate associations:Focusses associationsThis method focusses on a few highly relevant criterion variables. This can make use of validity generalization. Sets of correlationsThis method focusses on a broad range of criterion variables and computes the correlations between the test and many criterion variables. The degree to which the pattern of correlations ‘makes sense’ given the conceptual meaning of the construct is evaluated.Multitrait-...