METRICS IN SMALL-SIZED QURAN DATASET FOR BENFORD’S LAW

Autor:	M. Z. A. M. Jaffar, A. N. Zailan, N. H. Izamuddin
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	benford’s law quran small-sized dataset metric Applied mathematics. Quantitative methods T57-57.97 Mathematics QA1-939 Business mathematics. Commercial arithmetic. Including tables etc. HF5691-5716
Zdroj:	Matrix Science Mathematic, Vol 5, Iss 2, Pp 35-38 (2021)
Druh dokumentu:	article
ISSN:	2521-0831 2521-084X
DOI:	10.26480/msmk.01.2021.35.38
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/7477b16803cb42f19b7d8e016edb6a38 Zobrazit plný text záznamu View record in DOAJ