Comparison of selected tests for univariate normality based on measures of moments

Domański Czesław () and Szczepocki Piotr ()
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Domański Czesław: Department of Statistical Methods, The Faculty of Economics and Sociology, University of Lodz, Lodz, ; Poland .
Szczepocki Piotr: Department of Statistical Methods, The Faculty of Economics and Sociology, University of Lodz, Lodz, ; Poland .

Statistics in Transition New Series, 2020, vol. 21, issue 5, 151-178

Abstract: Univariate normality tests are typically classified into tests based on empirical distribution, moments, regression and correlation, and other. In this paper, power comparisons of nine normality tests based on measures of moments via the Monte Carlo simulations is extensively examined. The effects on power of the sample size, significance level, and on a number of alternative distributions are investigated. None of the considered tests proved uniformly most powerful for all types of alternative distributions. However, the most powerful tests for different shape departures from normality (symmetric short-tailed, symmetric long-tailed or asymmetric) are indicated.

Keywords: normality tests; Monte Carlo simulation; power of test. (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:21:y:2020:i:5:p:151-178:n:3

DOI: 10.21307/stattrans-2020-060

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