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

Journal Name:

  • European Journal of Pure and Applied Mathematics

Publication Year:

  • 2011

Key Words:

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AMS Codes:

Abstract (2. Language): 
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.
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  • 4
448-454
  • English

REFERENCES

References: 

[1] T Anderson and D Darling. A test of goodness of fit. Journal of the American Statistical
Association, 49(268):765–769, 1954.
[2] C Jarque and A Bera. A test for normality of observation and regression residuals. International
Statistical Review, 55(2):163–172, 1987.
[3] S Shapiro and M Wilk. An analysis of variance test for normality. Biometrica, 52(3 &
4):591, 1965.

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