Ultra-fine transformation of data for normality.

ABSTRACT: Normally distributed data is crucial for the application of large-scale statistical analysis. To statisticians, the most important assumptions of statistical users are the adequacy of the data and the normal distribution of the data. However, users are constantly forced to deal with unusual data. This includes changing the method used to be less sensitive to non-normal data or transforming that data to normal data. In addition, common mathematical transformation methods (for example, Box-Cox) do not work on complex distributions, and each method works on limited data shapes. In this paper, a novel approach is presented to transform any data into normally distributed data. We refer to our approach as the Ultra-fine transformation method. The article's novelty is that the proposed approach i

SUBMITTER: Hamasha MM 

PROVIDER: S-EPMC9118124 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature