This report demonstrates logistic regression using a diabetes dataset. The outcome is diabetes diagnosis (Yes/No), predicted by age, BMI, glucose level, physical activity, and family history.

Developed a reproducible data pipeline in R (using SQL) to analyze the relationship between median household income and cancer incidence rates across 50 states using API and CDC WONDER datasets. Executed advanced data wrangling with tidyverse and sf to merge health outcomes with geographical data, creating interactive leaflet visualizations for regional disparity assessment. Implemented statistical testing and residual analysis (linear regression) to investigate outliers, identifying specific geographic regions where health outcomes deviated significantly from economic predictions.

this is our final output