● Analyzed district-level NFHS-4 and NFHS-5 datasets using Python to evaluate public health and socio-economic indicators across India. ● Performed data cleaning, feature selection, missing value handling, data validation, exploratory data analysis (EDA), and data visualization using Pandas, Matplotlib, and Seaborn. ● Applied statistical hypothesis testing and regression techniques, including Shapiro-Wilk, Wilcoxon Signed-Rank, Multiple Linear Regression, Logit, and Probit models, to analyze district-level health outcomes. ● Interpreted and documented analytical findings on blood pressure, blood sugar, BMI, and anaemia, presenting data-driven insights from district-level health indicators.