Analysis of Personal Running Data
This is one of the projects I completed at Michigan Tech during MA4710 (Regression Analysis)
Throughout the course of this project, I was using running data collected from Garmin devices from two runners: Me and my wife, Leah.
An attempt was made to predict average speed based on metrics collected by wearable technology. Predictors include distance, average heart rate, cadence, time of day, elevation, and several others.
During this project, I discovered that you can calculate average speed based on stride length and cadence, so none of the final models contain both predictors together.
This project isn't completely finished (I never settled on a perfect final model) but serves as a good reference for the sort of model analysis I learned in the course.