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This work is cited by the following items of the Benford Online Bibliography:
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Eckhartt, GM and Ruxton, GD (2023). Investigating and preventing scientific misconduct using Benford’s Law. Research Integrity and Peer Review 8(1). DOI:10.1186/s41073-022-00126-w.
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Hsu, L and Berisha, V (2022). Does human speech follow Benford’s Law?. Preprint arXiv:2203.13352 [cs.CL]; last accessed April 2, 2022. DOI:10.48550/arxiv.2203.13352.
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MacDonald, DK (2021). Using Benford’s Law to Detect Fraud. Posted on dustinkmacdonald.com blog May 2; last accessed May 18, 2021.
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Moreau, VH (2021). Inconsistencies in Countries COVID-19 Data Revealed by Benford’s Law’. Model Assisted Statistics and Applications 16(1), pp. 73-79. DOI:10.3233/MAS-210517.
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Ollén, ER and Wennberg, J (2021). Assessing practicalities of Benford's Law: A study of the law's potential to detect fraud in transactional data. Bachelor thesis, Dept. of Economics, Lund University.
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Parreño, SJE (2023). Assessing the quality of dengue data in the Philippines using Newcomb-Benford law. Sapienza: International Journal of Interdisciplinary Studies 4(3). DOI:10.51798/sijis.v4i3.662.
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Pinilla, J, López-Valcárcel, BG, González-Martel, C and Peiro, S (2018). Pinocchio testing in the forensic analysis of waiting lists: using public waiting list data from Finland and Spain for testing Newcomb-Benford’s Law. BMJ open,8(5), pp. 1-6. ISSN/ISBN:2044-6055. DOI:10.1136/bmjopen-2018-022079.
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