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Bootstrap Analysis in Linear Regression with Missing Data
This article is part of Statistical Modeling and Simulation Course tasks
STA320 Final
STA 320 Team 2 Final
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House Price Prediction
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Life Expectancy Analysis and Prediction Using Public Health Indicators in R
This project performs a data-driven analysis of global life expectancy using R, combining exploratory data analysis, correlation analysis, and regression modeling. Key determinants such as schooling, GDP, and disease prevalence are identified, and a multiple linear regression model is developed to quantify their impact. The model achieves strong explanatory power (R² ≈ 0.77) and reliable predictive performance (RMSE ≈ 4.49), demonstrating the influence of socioeconomic and healthcare factors on life expectancy.