Conducted comprehensive statistical analysis of alcohol-related motor vehicle fatalities using R programming and advanced data visualization techniques. The project examines patterns, trends, and correlations in traffic safety data to provide insights for public health policy and prevention strategies.
Technical Achievements:
- Performed extensive exploratory data analysis on national traffic fatality databases
- Created interactive visualizations and statistical models to identify risk factors
- Built reproducible research workflows using R Markdown for data processing and reporting
- Implemented time series analysis to track fatality trends over multiple years
- Developed geographic mapping visualizations to identify high-risk regions
- Published findings as an interactive web report using GitHub Pages
Research Impact: The analysis revealed significant patterns in alcohol-related fatalities across different demographics, time periods, and geographic regions. The project provides data-driven insights that can inform evidence-based policy decisions for traffic safety improvement and alcohol-related prevention programs.