Cross Reference Up
Nigrini, MJ (2015). Detecting Fraud and Errors Using Benford’s Law. In: S.J. Miller (ed.) Benford's Law: Theory and Applications, Princeton University Press: Princeton, NJ, pp. 191-211.
This work is cited by the following items of the Benford Online Bibliography:
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| Adam, A and Tsarsitalidou, S (2022). Data misreporting during the COVID19 crisis: The role of political institutions. Economics Letters 213, p. 110348. DOI:10.1016/j.econlet.2022.110348. |  |
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| Burns, BD (2020). Do people fit to Benford’s law, or do they have a Benford bias?. Proceedings of the 42nd Annual Virtual Meeting of the Cognitive Science Society, pp. 1729-1735. | |
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| Cabarle, C (2018). Using Benford’s law to predict the risk of financial statement fraud in equity crowd funding offerings. Proceedings of 2018 Engaged management scholarship conference, Philadelphia, PA.. DOI:10.2139/ssrn.3240900. | |
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| Cabarle, C (2019). Predicting the Risk of Fraud in Equity Crowdfunding Offers and Assessing the Wisdom of the Crowd. PhD Thesis, Temple University, ProQuest Dissertations Publishing, 2019. 13863507. | |
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| Cerioli, A, Barabesi, L, Cerasa, A, Menegatti, M and Perrotta, D (2019). Newcomb-Benford law and the detection of frauds in international trade. Proceedings of the National Academy of Sciences 116(1), pp. 106-115. DOI:10.1073/pnas.1806617115. | |
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| Chi, D (2024). The Influence of Statistical Information on Number Estimation Under Uncertainty: Why Do People Present Benford Bias?. PhD Thesis, School of Psychology, Faculty of Science, University of Sydney. | |
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