Univariate and multivariate distributions of the job descriptive index's measures of job satisfaction

Abstract

This study examines the univariate and multivariate distributions of the Job Descriptive Index's (JDI) scales for job satisfaction with work, supervision, pay, promotion, and co-workers. The results indicate that the sample distributions of four of the five scales differ significantly from normality. The exception is satisfaction with work. After normalizing square-root transformations were applied to the nonnormal scales, the results of a test for multivariate normality indicated that the transformed sample data for the satisfaction scales reasonably approximate multivariate normality. The implication for organizational researchers is that the use of univariate statistical procedures that are sensitive to nonnormality is questionable in analyses involving the JDI scales. When it is appropriate to analyze the scales jointly, normalizing transformations are recommended to induce approximate multivariate normality for the joint distribution.