Are public medical schools in Texas truly merit-based, or do their admissions decisions reflect systemic biases? University of Austin Professor David Puelz and his students confront one of the most pressing and controversial questions in higher education: Do race and gender significantly influence who gets into medical school—even after accounting for academic qualifications? Using real admissions data from six Texas medical schools, UATX students apply logistic regression modeling to examine the probability of acceptance across different demographic groups.
What you’ll learn in this video:
1. How to build and interpret a logistic regression model in R
2. What “odds ratios” reveal about disparities in acceptance rates
3. How to isolate the effect of race and gender by controlling for academic metrics
4. Why statistical significance matters—and what it tells us about fairness in admissions
5. The real-world implications of selecting future doctors based on non-merit factors
Share this post