This project explores a health insurance dataset to uncover patterns in medical charges and health behaviors. Using Python, I applied univariate and bivariate analyses to identify key trends, then conducted Welch’s t-test and Kruskal-Wallis tests to evaluate the impact of smoking and regional factors on healthcare costs and BMI. The results provided actionable insights for premium adjustments, regional health planning, and targeted wellness programs.