Predictive Regression Modeling & Database Systems/Extraction (R/SQL/PostgreSQL coursework/projects)
Built and validated predictive regression models using statistical analyses to support data-driven insights. Applied hypothesis testing techniques including t-tests and ANOVA to assess statistical significance of model relationships. Developed data extraction workflows from PostgreSQL to support downstream analysis and modeling tasks. • Implemented simple linear regression and evaluated fit using R² (e.g., R² = 0.97) and sum of squares metrics (SST, SSR, SSE). • Used ANOVA tables and t-tests at α = 0.05 to determine statistical significance. • Designed SQL/PostgreSQL data extraction workflows for use in R and Python analytics. • Focused on relational integrity and efficient querying for large-scale data analysis.