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Metrics in small-sized Quran dataset for Benford’s law

Benford’s law is widely applied in testing anomalies in various dataset, including accounting fraud detection and population numbers. It is a statistical regularity, which is said that it works better with larger datasets that span large orders of magnitude distributed in a non-uniform way. In this...

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Main Authors: M. Jaffar, M. Z. A., Zailan, A. N., Izamuddin, N. H.
Format: Article
Published: Zibeline International Publishing 2021
Online Access:http://psasir.upm.edu.my/id/eprint/94173/
https://matrixsmathematic.com/msmk-02-2021-35-38/
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spelling my.upm.eprints.941732023-05-09T02:03:50Z http://psasir.upm.edu.my/id/eprint/94173/ Metrics in small-sized Quran dataset for Benford’s law M. Jaffar, M. Z. A. Zailan, A. N. Izamuddin, N. H. Benford’s law is widely applied in testing anomalies in various dataset, including accounting fraud detection and population numbers. It is a statistical regularity, which is said that it works better with larger datasets that span large orders of magnitude distributed in a non-uniform way. In this study, we examine the potential metrics in small-sized Quran dataset that are applicable for the Benford’s law. Against our expectations, we find that the Quran dataset conforms to the Benford’s law. We provide evidence that metrics such as total paragraph per chapter and total verse per chapter conform to Benford’s distribution. However, total verse is closer to Benford’s law prediction compared to total paragraph. Zibeline International Publishing 2021 Article PeerReviewed M. Jaffar, M. Z. A. and Zailan, A. N. and Izamuddin, N. H. (2021) Metrics in small-sized Quran dataset for Benford’s law. Matrix Science Mathematic, 5 (2). art. no. 2. 35 - 38. ISSN 2521-0831; ESSN: 2521-084X https://matrixsmathematic.com/msmk-02-2021-35-38/ 10.26480/msmk.02.2021.35.38
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Benford’s law is widely applied in testing anomalies in various dataset, including accounting fraud detection and population numbers. It is a statistical regularity, which is said that it works better with larger datasets that span large orders of magnitude distributed in a non-uniform way. In this study, we examine the potential metrics in small-sized Quran dataset that are applicable for the Benford’s law. Against our expectations, we find that the Quran dataset conforms to the Benford’s law. We provide evidence that metrics such as total paragraph per chapter and total verse per chapter conform to Benford’s distribution. However, total verse is closer to Benford’s law prediction compared to total paragraph.
format Article
author M. Jaffar, M. Z. A.
Zailan, A. N.
Izamuddin, N. H.
spellingShingle M. Jaffar, M. Z. A.
Zailan, A. N.
Izamuddin, N. H.
Metrics in small-sized Quran dataset for Benford’s law
author_facet M. Jaffar, M. Z. A.
Zailan, A. N.
Izamuddin, N. H.
author_sort M. Jaffar, M. Z. A.
title Metrics in small-sized Quran dataset for Benford’s law
title_short Metrics in small-sized Quran dataset for Benford’s law
title_full Metrics in small-sized Quran dataset for Benford’s law
title_fullStr Metrics in small-sized Quran dataset for Benford’s law
title_full_unstemmed Metrics in small-sized Quran dataset for Benford’s law
title_sort metrics in small-sized quran dataset for benford’s law
publisher Zibeline International Publishing
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/94173/
https://matrixsmathematic.com/msmk-02-2021-35-38/
_version_ 1768009382445973504
score 13.211869

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