Evaluating correlations in studies of personality and behavior: Beyond the number of significant findings to be expected by chance

When large numbers of statistical tests are computed, such as in broad investigations of personality and behavior, the number of significant findings required before the total can be confidently considered beyond chance is typically unknown. Employing modern software, specially written code, and new procedures, the present article uses three sets of personality data to demonstrate how approximate randomization tests can evaluate (a) the number of significant correlations between a single variable and a large number of other variables, (b) the number of significant correlations between two large sets of variables, and (c) the average size of a large number of effects. Randomization tests can free researchers to fully explore large data sets and potentially have even wider applicability.