Recovery and wearable metrics
Collaborative statistics coursework
A group study of recovery, heart-rate variability, workouts, and fitness level in a simulated wearable dataset.
- Status
- Coursework · April 2026
- Kind
- Data & geometry
- Stack
- R · dplyr · ggplot2 · Statistical analysis
BUILD NOTES / Coursework · April 2026Recovery and wearable metrics
Project overview · not an interface capture
Collaborative statistics coursework
R / dplyr / ggplot2Project overview · not an interface capture
The problem
The project asked which variables are associated with recovery and how to distinguish a visible pattern from evidence that supports a broader conclusion.
What was built
- A collaborative report with exploratory plots, bootstrap uncertainty, a two-sample t-test, and one-way ANOVA.
- Two regression models compared on held-out data in the team’s analysis.
- My contribution: the introduction, dataset description, and final document compilation, alongside review of the completed report.
What I learned
Clear dataset framing and attribution matter. Simulated records can support an exercise in statistical methods without establishing a health or training outcome.