Political Polling Teaching Article
Political Polling Teaching Article
Peer-reviewed teaching article using the 1936 Literary Digest poll to help students explore data cleaning, sampling bias, and polling adjustment.
Executive Summary
Taking the Next Step in Exploring the Literary Digest 1936 Poll is a peer-reviewed teaching article published in the Journal of Statistics and Data Science Education. The article revisits the famous 1936 Literary Digest poll, which is often used to introduce sampling bias, and develops additional classroom activities around data acquisition, cleaning, validation, visualization, and adjustment methods.
I contributed to the data preparation, review, and early drafting process. My work supported the article’s broader goal: helping instructors turn a familiar historical polling example into a richer learning opportunity for statistics and data science students.
Project Highlights
- Contributed to a peer-reviewed statistics education article focused on sampling bias, data validation, and polling adjustment.
- Supported data cleaning and review of historical polling data from the 1924–1936 Literary Digest presidential election polls.
- Helped develop instructional materials that invite students to work with imperfect data, evaluate bias, and compare adjustment strategies.
Methods & Approach
The article uses the Literary Digest polling data as a historical case study for teaching statistical thinking. Beyond identifying the poll’s well-known sampling and nonresponse bias, the paper explores how students can work with original data sources, identify data quality issues, visualize prediction errors, and evaluate simple adjustment methods.
My contributions centered on supporting the data workflow and manuscript development. This included cleaning and checking historical data, reviewing analysis materials, and contributing to early drafts of the paper.
Deliverables
Peer-Reviewed Paper
A published statistics education article that provides instructors with classroom activities and supporting materials for teaching data cleaning, sampling bias, and polling adjustment through the 1936 Literary Digest poll.