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This work is cited by the following items of the Benford Online Bibliography:
Note that this list may be incomplete, and is currently being updated. Please check again at a later date.
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/s4107302200126w.





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.





MacDonald, DK (2021). Using Benford’s Law to Detect Fraud. Posted on dustinkmacdonald.com blog May 2; last accessed May 18, 2021.





Moreau, VH (2021). Inconsistencies in Countries COVID19 Data Revealed by Benford’s Law’. Model Assisted Statistics and Applications 16(1), pp. 7379. DOI:10.3233/MAS210517.





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.





Parreño, SJE (2023). Assessing the quality of dengue data in the Philippines using NewcombBenford law. Sapienza: International Journal of Interdisciplinary Studies 4(3). DOI:10.51798/sijis.v4i3.662.





Pinilla, J, LópezValcárcel, BG, GonzálezMartel, 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 NewcombBenford’s Law. BMJ open,8(5), pp. 16. ISSN/ISBN:20446055. DOI:10.1136/bmjopen2018022079.




