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The Journal of Statistics and Management Systems (JSMS) is a world leading journal publishing high quality, rigorously peer-reviewed original research on theoretical and applied statistics and management systems since 1998. The scope is intentionally broad, but papers must make a novel contribution to the field to be considered for publication. Topics include, but are not limited to, the following: • Statistics • Applied Statistics • Industrial Statistics • Statistical Inference • Interdisciplinary role of Statistics • Actuarial Sciences • Decision Sciences • Managerial Aspects • Management Sciences • Management Information Systems

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Open Access Research Article

A new goodness of fit test for normal distribution based on the negative cumulative extropy

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pp. 855–878Vol. 28Issue 5July 2025DOI: 10.47974/JSMS-1387XML
Received:
13 Dec 2023
Published Online:
10 May 2025
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1387
Pages:
855–878

Abstract

In recent years, extropy has emerged as a compelling alternative measure of uncertainty in statistical analysis. This paper focuses on the negative cumulative residual extropy, as introduced by Tahmasebi and Toomaj [28], and leverages this concept to develop a novel goodness-of-fit test for normality. We rigorously examine the statistical properties of this new test statistic, including its mean and variance. Furthermore, we establish the percentiles of the test statistic’s distribution, allowing for practical implementation. To assess its effectiveness, we evaluate the power of the proposed test against a range of alternative distributions. Our simulation results reveal that the new test exhibits competitive power compared to existing methods. The test is computationally straightforward, and we demonstrate its practical application through the analysis of a real-world dataset.

Keywords

Subject Classifications

62G1062G30

References

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