The Software Behind the Stats: A Student Exploration of Software Trends Across Disciplines
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ID: 282508
2025
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Abstract
This paper presents a student-led activity designed to explore the use of
statistical software in academic research across economics, political science,
and statistics. Students reviewed replication files from major journals and
repositories, gaining hands-on experience with reproducible workflows while
contributing to cross-disciplinary datasets. Web-scraped metadata and student
data collection, together covering more than 10,000 papers, reveal clear
disciplinary patterns: Stata remains dominant in economics, while R is
increasingly popular in political science and is the standard in statistics.
Within the social sciences, a growing number of articles also use multiple
software platforms within a single manuscript. Students reported increased
understanding of academic workflows and greater awareness of software diversity
in quantitative research. The activity is easy to adapt across course levels
and disciplines, and we offer suggestions for follow-up assignments that
reinforce key concepts in reproducibility and data fluency. The resulting
insights into current software practices are also valuable for instructors
seeking to align their teaching with evolving trends in research.
| Reference Key |
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| Authors | Elizabeth Upton; Xizhen Cai; Pamela Jakiela; Owen Ozier; Shyam Raman |
| Journal | arXiv |
| Year | 2025 |
| DOI |
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