Hello World!

This repository was created by Carrie Feng, Oliver Meek, and Tara Udani as a final project for DS 2023. For this project, we used a simulated dataset regarding ACLR recovery. The simulated data was based on patient data compiled by School of Data Science and the Department of Kinesiology at the University of Virginia. We explored the progression of flexion and extension strength throughout recovery, as well their relationship to psychological readiness. We found that patients typically have stronger flexion than extension after ACLR, but that recovery is nonlinear and about more than just strength.

We learned how to work with large, messy, longitudinal data. We learned how to extract meaningful conclusions from data and communicate them to a non-technical audience in a vsiually appealing way. These skills, especially the communication part, will serve as assets in our larger data science careers. As data scientists, it's our job to bridge the gap between people and numbers.