This presentation provides a comprehensive overview of Simple Linear Regression, covering both theoretical foundations and practical R implementation. Key topics include Ordinary Least Squares (OLS) estimation, interpreting the Coefficient of Determination R^2, and performing statistical inference on model coefficients. The slides also demonstrate how to validate model assumptions through residual diagnostics and provide a real-world example using study hours to predict exam scores.