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 focuses on three of the most common data transformations used to improve normality: (1) square root; (2) logarithmic; and (3) inverse transformations. It is recommended that researchers always examine and understand data prior to performing analyses, and that they then know the requirements of the data analysis technique to be used. Data transformation should be used with care, and never unless there is a clear reason, and the researcher must ensure that the variable is anchored at a place where the transformation will have the optimal effect. (SLD)