Life scientists often struggle to normalize non-parametric data or ignore normalization prior to data analysis. Based on statistical principles, logarithmic, square-root and arcsine transformations are commonly adopted to normalize non-parametric data for parametric tests. Several other transformations are also available for normalizing data. However, for many, identification of right transformation for non-parametric data is a tricky job. The objective of this paper is to develop a SAS program that identifies right transformation and normalize non-parametric data for regression analysis. To achieve this objective, PROC SQL, PROC TRANSREG, PROC REG, PROC UNIVARIATE, PROC STDIZE, PROC CORR, PROC SGPLOT, PROC IMPORT and PROC PRINT of SAS are utilized in this paper. Finally, SAS MACROS are developed on this code for reuse without hassles.
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