This presentation provides an introduction to Simple Linear Regression, a fundamental concept in statistical modeling. It covers key aspects such as: Understanding the relationship between two variables using a straight line. Interpreting the slope and intercept of the regression equation. Assumptions behind linear regression, including linearity, independence, homoscedasticity, and normality. Fitting a linear model to data using R. Visualizing regression results with plots. Evaluating model performance through R-squared and residual analysis. The presentation is ideal for beginners and intermediate learners who want to understand the basics of linear regression and its practical implementation in R.