Taking the Next Step in Exploring the <i>Literary Digest</i> 1936 Poll

While many instructors are aware of the Literary Digest 1936 poll as an example of biased sampling methods, this article details potential further explorations for the Digest’s 1924–1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to basic data literacy and visualization skills, to exploring one or more methods of adjustment to account for bias based on information collected at that time. Students can also compare how those methods would have performed. One option could be to give introductory students a first look at the idea of “sampling adjustment” and how this principle can be used to account for difficulties in modern polling, but the context is rich in other opportunities that can be discussed at various times in the course or in more advanced sampling courses. Supplementary materials for this article are available online.

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Publication Details

Journal
Journal of Statistics and Data Science Education
Published
2024-08-22
DOI
https://doi.org/10.1080/26939169.2024.2395505
Primary Topic
Race, History, and American Society
Type
article
Field-Weighted Citation Impact
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article

Taking the Next Step in Exploring the Literary Digest 1936 Poll

Andrew Kerr, Beth Chance, Jett Palmer
Journal of Statistics and Data Science Education
Race, History, and American Society
article

Taking the Next Step in Exploring the Literary Digest 1936 Poll

Andrew Kerr, Beth Chance, Jett Palmer
article en

Abstract

While many instructors are aware of the Literary Digest 1936 poll as an example of biased sampling methods, this article details potential further explorations for the Digest’s 1924–1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to basic data literacy and visualization skills, to exploring one or more methods of adjustment to account for bias based on information collected at that time. Students can also compare how those methods would have performed. One option could be to give introductory students a first look at the idea of “sampling adjustment” and how this principle can be used to account for difficulties in modern polling, but the context is rich in other opportunities that can be discussed at various times in the course or in more advanced sampling courses. Supplementary materials for this article are available online.

Journal of Statistics and Data Science Education
California Polytechnic State University (US)
Openalex Percentile: Top 79%
Race, History, and American Society
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