Luis Zapata
Research Mentor: Murali Mani
Mentor Department: University of Michigan Flint, Other
Author(s): Luis Zapata, Ehsan Haque, Murali Mani
Session: Session 7 (4:00 PM – 4:50 PM)
Presentation Type: Poster 22
Abstract
This project, An Ounce of Computing in Statistics Courses, explores how a guided, R-based “stats studio†can lower barriers to data analysis for students in non-CS courses while still building genuine computational fluency. It focuses on a front-end application that makes core statistical workflows like importing data, cleaning and understanding variables, visualizing distributions, and running standard analyses such as confidence intervals, hypothesis tests, and regression, clickable and concept-first, with R handling transparent, reproducible computation behind the scenes. A structured “Guided Lab Mode†leads students through an eight-step process, supported by features like an automatic data-dictionary panel, assumption checks, and a report generator that produces submission-ready outputs with code appendices for students to follow along. Over the year, the UROP student refined this workflow with real course datasets and implemented a minimal viable product, a Shiny app for R studio, for an introductory statistics courses for non-CS majors, providing instructors more consistent, reproducible student work and giving students a gentler on-ramp into statistical computing.
