The Software Behind the Stats: A Student Exploration of Software Trends Across Disciplines

📅 2025-04-09
📈 Citations: 0
Influential: 0
📄 PDF

career value

158K/year
🤖 AI Summary
This study investigates cross-disciplinary trends in statistical software adoption across economics, political science, and statistics. Method: We systematically replicated and coded open-source code and data files from over 10,000 peer-reviewed papers, integrating web-crawled metadata, manual annotation, qualitative coding, and frequency analysis to construct the first student-led, interdisciplinary database of statistical software usage. Contribution/Results: We introduce the “multi-platform collaborative analysis” paradigm, revealing that Stata remains dominant in economics, while R has become the preferred tool in political science and statistics; moreover, over 30% of social science studies employ two or more software packages synergistically. The project significantly enhances students’ reproducibility capacity and data literacy, fostering concurrent updates in pedagogy and research practice.

Technology Category

Application Category

📝 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.
Problem

Research questions and friction points this paper is trying to address.

Explores statistical software trends in economics, political science, statistics
Analyzes 10,000+ papers for disciplinary software usage patterns
Enhances student understanding of reproducibility and software diversity
Innovation

Methods, ideas, or system contributions that make the work stand out.

Student-led review of replication files
Web-scraped metadata and student data collection
Analysis of disciplinary software usage patterns
🔎 Similar Papers
No similar papers found.
E
Elizabeth Upton
Department of Mathematics and Statistics, Williams College
X
Xizhen Cai
Department of Mathematics and Statistics, Williams College
P
Pamela Jakiela
Department of Economics, Williams College; CGD; IZA; BREAD; and J-PAL
O
Owen Ozier
Department of Economics, Williams College; IZA; BREAD; and J-PAL
S
Shyam Raman
Department of Economics, Williams College