Statistical Fallacies in Claims about ‘Massive and Widespread Fraud’ in the 2020 Presidential Election: Examining Claims Based on Aggregate Election Results

DOI: 10.1080/2330443X.2023.2289529

65 Pages Posted: 29 Mar 2021 Last revised: 30 Nov 2023

See all articles by Bernard Grofman

Bernard Grofman

University of California, Irvine

Jonathan Cervas

Carnegie Mellon University

Date Written: November 20, 2023

Abstract

Years after the election, a substantial portion of the electorate, including a significant majority of Republican voters and numerous Republican officials, continue to believe that the 2020 election was stolen. This essay reviews claims of alleged massive electoral fraud in the 2020 U.S. presidential election. These claims are based on analyses of aggregate-level election data. Although the underlying data in each of the thirteen claims we review are accurately described, our review reveals that the interpretations of the election data, which suggest massive fraud, are based on invalid statistical or illogical reasoning. In summary, the conclusions about fraud derived from these statistical analyses are categorically incorrect. We believe this article will serve as a valuable educational tool for the press, the public, and students. It underscores the dangers of misusing statistical inference and emphasizes the importance of accurate statistical analysis in political discourse. By discussing statistical fallacies in a non-technical manner, we aim to make our critiques accessible to a broad, non-specialist audience. This significantly contributes to the understanding of misinformation and its impact on democracy and public trust in electoral processes.

Keywords: voter fraud; elections

Suggested Citation

Grofman, Bernard and Cervas, Jonathan, Statistical Fallacies in Claims about ‘Massive and Widespread Fraud’ in the 2020 Presidential Election: Examining Claims Based on Aggregate Election Results (November 20, 2023). DOI: 10.1080/2330443X.2023.2289529, Available at SSRN: https://ssrn.com/abstract=3794738 or http://dx.doi.org/10.2139/ssrn.3794738

Bernard Grofman

University of California, Irvine ( email )

School of Social Sciences
SSPB 2291
Irvine, CA 92697
United States
19497331094 (Phone)

HOME PAGE: http://www.socsci.uci.edu/~bgrofman/

Jonathan Cervas (Contact Author)

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

HOME PAGE: http://jonathan Cervas.com

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