A Novel Normality Test Using an Identity Transformation of the Gaussian Function

Authors

  • Oguz Akbilgic
  • J. Andrew Howe Tennessee Valley Authority

Keywords:

normality test, Gaussian distribution, probability distributions

Abstract

Normality is the most frequently required assumption for statistical techniques. Thus, evaluation of the normality assumption is the first step of many statistical analyses. Although there are many normality tests in the literature, none dominate for all conditions. This paper introduces a novel normality test, and its performance is compared with some of the other normality tests via a Monte Carlo simulation study. Tests are evaluated according to the Type I error and Power.

Author Biography

J. Andrew Howe, Tennessee Valley Authority

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How to Cite

Akbilgic, O., & Howe, J. A. (2011). A Novel Normality Test Using an Identity Transformation of the Gaussian Function. European Journal of Pure and Applied Mathematics, 4(4), 448–454. Retrieved from https://www.ejpam.com/index.php/ejpam/article/view/634

Issue

Vol. 4 No. 4: (October 2011)

License

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European Journal of Pure and Applied Mathematics will be Copyright Holder.