Fact-Check: "Joe Biden's presidential election results did not follow Benford's law"
What We Know
Benford's Law is a statistical principle that predicts the frequency distribution of the first digits in many real-life sets of numerical data. According to a report by Kossovsky and Miller, the analysis of the 2020 presidential election data indicated that Joe Biden's vote counts did not conform to the expected distribution outlined by Benford's Law. This claim has been widely circulated, particularly among those questioning the legitimacy of the election results.
However, other analyses, such as those presented in a paper from the University of Michigan, argue that applying Benford's Law to election data can be misleading. The authors caution against inappropriate applications of the law, highlighting that electoral data can be influenced by various factors that do not align with the assumptions of Benford's Law.
Furthermore, Reuters reported that deviations from Benford's Law do not inherently indicate fraud. They emphasized that while some datasets may not follow the law, this does not provide conclusive evidence of electoral misconduct.
Analysis
The claim that Biden's election results did not follow Benford's Law is supported by certain analyses, but it is essential to consider the context and methodology of these studies. The Kossovsky and Miller report presents a detailed examination of the data, but it is crucial to recognize that their findings are not universally accepted. Critics, including those from the University of Michigan, argue that the application of Benford's Law to election data is inappropriate due to the unique nature of voting patterns and the influence of various demographic and geographic factors.
The Reuters article provides a balanced perspective, noting that while some data may deviate from Benford's expectations, such deviations alone do not imply fraud. This aligns with the findings from the research published on ResearchGate, which suggests that deviations can occur in legitimate data due to numerous factors, including voter turnout and demographic shifts.
The reliability of the sources is mixed. The Kossovsky and Miller report is a formal analysis, but it has been critiqued for its methodology. In contrast, the University of Michigan paper is peer-reviewed and offers a more cautious interpretation of Benford's Law in electoral contexts, making it a more credible source for understanding the limitations of applying this statistical principle to election data.
Conclusion
The claim that Joe Biden's presidential election results did not follow Benford's Law is Partially True. While there are analyses indicating deviations from the expected distribution, these findings do not conclusively prove electoral fraud. The application of Benford's Law to election data is contentious, and many experts caution against drawing definitive conclusions based solely on statistical anomalies. Therefore, while the claim has some basis in observed data, it lacks the necessary context to be considered a definitive indicator of fraud.
Sources
- REPORT ON BENFORD'S LAW ANALYSIS OF 2020 ...
- Inappropriate Applications of Benfordβs Law Regularities to ...
- Deviation from Benford's Law does not prove election fraud
- Why do Biden's votes not follow Benford's Law?
- Do vote counts for Joe Biden in the 2020 election violate ...
- Benford's law and the 2020 US presidential election
- Was There Any Widespread Fraud in 2020 Presidential Election ...
- Vote Data Patterns used to Delegitimize the Election Results