Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests (e.g., multiple regression, ANOVA) can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric…

The goal of this Digest is to explore some of the issues involved in data transformation, with particular focus in the use of data transformation for the normalization of variables. The Digest is intended to serve as an aid to researchers who do not have extensive mathematical backgrounds or who had not had extensive exposure to this issue. It…

Data transformations are commonly used tools in quantitative analysis of data. However, data transformations can be a mixed blessing to researchers, improving the quality of the analysis while at the same time making the interpretation of the results difficult. Few, if any, statistical texts discuss the tremendous influence a distribution's…