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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Zibeline International Publishing
2021
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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 |
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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/ |
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1768009382445973504 |
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13.18916 |