The Effects of Minimum Values

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 minimum value has on the outcome of a transformation. The goal of this paper is to promote thoughtful and informed use of data transformation. The focus is on three common data transformations: square root, logarithmic, and inverse transformations. All three are curvilinear transformations that change the nature of the variable to a certain extent. Examples illustrate the importance of the minimum value of a distribution should the researcher intend to use data transformation on that variable. (Contains 10 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document