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Transformations with Right Skew Data

The basic assumption of statistical analysis is that the data have normally distributed. When analyzing data do not match the assumptions of the conventional method of analysis, there are two choices; transform the data to fit the assumptions or develop some new robust methods of analysis. If a satisfied transformation can find, it will almost always be easier to use it rather than to develop a new method of analysis. The well-known Box-Cox transformations often used in previous studies. However, they are not always applicable, they should be used with caution in some cases such as failure time and survival data. Because the some observations in the sets of right skew data may be zero, the Box-Cox transformations are not appropriate. In this paper, the several transformations are investigated for some sets of right skew data. They performs few better than the Box-Cox transformations in sense of normality and homogeneity of variances for several groups of data in some situations.