This podcast explores the essential mechanics of simple linear regression, a statistical method used to predict a dependent variable based on a single independent variable. The discussion moves beyond the basic formula (Y=a+bX) to examine why Ordinary Least Squares (OLS) is used to find the "line of best fit" by minimizing the sum of squared residuals.