Measures of relative position, such as Standard Scores and Percentile Ranks provide a means for “ranking” individuals in a given group. The computation and interpretation of percentile ranks in normal and non-normal distributions vary.

To determine the extent to which two variables are related, we compute correlation coefficients. There is more that one type of correlation coefficient, but they have common properties and are interpreted similarly. Pearson’s r was given special attention in Chapter 10. Relationships between pairs of variables can be depicted with bivariate scatterplots. As an aid to interpret the r, the Coefficient of Determination, r squared, was introduced. Once converted to r squared, negative correlations are interpreted in the same way as positive correlations. The greater the rsquared value, the stronger the relationship. The chapter concluded by making mention of regression and factor analysis as correlational techniques that are frequently used in validation research.

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