Informatics and Applications
2023, Volume 17, Issue 1, pp 1827
TESTS FOR NORMALITY OF THE PROBABILISTIC DISTRIBUTION WHEN DATA ARE ROUNDED
 V. G. Ushakov
 N. G. Ushakov
Abstract
Tests for normality are less sensitive to the data rounding than, for example, tests for exponentiality but among normality tests, the sensitivity is very different. In this paper, the authors find out which tests are more and which ones are less sensitive. The authors show that tests based on sample moments are much more robust with respect to the data rounding than tests based on order statistics (in contrast to the robustness with respect to outliers where order statistics are more robust than sample moments). This, however, only applies to the probability of Type I error. The probability of Type II error is very insensitive to the data rounding for all normality tests.
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[+] About this article
Title
TESTS FOR NORMALITY OF THE PROBABILISTIC DISTRIBUTION WHEN DATA ARE ROUNDED
Journal
Informatics and Applications
2023, Volume 17, Issue 1, pp 1827
Cover Date
20230410
DOI
10.14357/19922264230103
Print ISSN
19922264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
normal distribution; test for normality; rounded data; significance level; MonteCarlo simulation
Authors
V. G. Ushakov , and N. G. Ushakov ,
Author Affiliations
Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, 152 Leninskie Gory, GSP1, Moscow 119991, Russian Federation
Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 442 Vavilov Str., Moscow 119333, Russian Federation
Institute of Microelectronics Technology and HighPurity Materials of the Russian Academy of Sciences,
6 Academician Osipyan Str., Chernogolovka, Moscow Region 142432, Russian Federation
Norwegian University of Science and Technology, 15A S. P. Andersensvei, Trondheim 7491, Norway
