This analysis, completed for QMSS GR5015: Data Analysis for the Social Sciences at Columbia University, investigates how human development influences gender inequality worldwide. Using the QoG Basic Cross-Section Dataset (2024), the study applies regression models to test whether higher development levels predict lower gender inequality and whether female literacy mediates this relationship. Beyond the primary model, the project examines the mismatch between economic wealth and corruption levels across nations to illustrate how institutional strength, rather than income alone, shapes social progress. By integrating statistical modeling and cross-country comparison, the project demonstrates how data-driven approaches can uncover structural patterns behind inequality and governance.