Highlights
What I built
- Data cleaning, visualization, and model exploration in one analysis workflow.
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Data ScienceArchived
Health Outcomes Analysis
Socioeconomic health outcomes analysis for an OIDD capstone.
Course project using statistical and ML tooling to analyze relationships between socioeconomic factors and poor health outcomes.
- Date
- Course project
- Signal
- Data
- Build stage
- Archived
- Stack
- Python, Pandas
dataanalysiscoursework
Build snapshot
Project notes
Architecture
How the system works
- Dataset prep -> feature analysis -> model fitting -> interpretation.
Challenges
What made it hard
- Balancing statistical rigor with interpretable outputs under course timeline.
Lessons
What I learned
- Communicating assumptions is as important as model performance.
Stack / materials
PythonPandasSeabornDecision Trees
- Included for context, not as a flagship engineering project.