This project conducts a comprehensive assessment of South Dakota's economic health relative to broader United States national trends. Utilizing descriptive, predictive, and prescriptive analytics, the study evaluates the localized impacts of gross domestic product fluctuations, median household income, and minimum wage policies to provide actionable insights for policymakers, businesses, and investors. The analysis was conducted using Python libraries including Pandas, NumPy, Matplotlib, Seaborn, and Statsmodels to extract, clean, and analyze economic datasets from the Federal Reserve Economic Data.

Through multiple linear regression and policy simulations, the analysis reveals that while South Dakota's median household income tracks higher than the national average, it remains vulnerable due to wage stagnation failing to keep pace with inflation. Predictive modeling indicates that a 15 percent increase in the minimum wage serves as the most effective simulated policy intervention, projected to boost median income by 8.6 percent. Furthermore, a simulated 10 percent increase in agriculture driven gross domestic product raises income by 5.27 percent, underscoring the state's heavy reliance on farming and the need for economic diversification. The complete methodology, statistical summaries, and data visualizations can be reviewed in the embedded PDF.