An Open Sourced Software for Data Transformation and an Application on Simulated Data

In this study, it is aimed to develop a new user-friendly web-based software to ensure the normal distribution of the new data set obtained by applying various mathematical transformations to data sets that do not meet the normal distribution from parametric hypothesis testing conditions. The web based software is developed by Shiny web framework, which is an open source R package. In the web-based software, arcsinh (x), Box-Cox, Exponential, Lambert W (h type), Lambert W (s type), Logarithmic, Square root, Yeo-Johnson data transformation methods are used. The software also allows us to decide on the best conversion for the data set to be transformed by calculating the Pearson P test statistic, which chooses on the best method in the methods used. This is done by selecting the conversion with the smallest Pearson P statistic. In order to evaluate the outputs of the software, a data set with three variables was derived with the Cauchy, gamma, Weibull distributions respectively and 500 samples were used for each distribution. The developed software is novel user-friendly web-based software that enables researchers to get more accurate results in their work and to obtain data transformation methods that provide parametric test assumptions known as more powerful tests.