The normal equations for simple linear regression are a system of two linear equations used to find the optimal intercept and slope that minimize the sum of squared residuals. They are derived from the ordinary least squares (OLS) method and can be expressed in scalar or matrix form.Solver

Multiple Linear Regression (MLR) models the linear relationship between a continuous dependent variable and two or more independent (explanatory) variables. Using the equation, it predicts outcomes based on multiple factors. Key assumptions include linearity, constant variance of residuals, and low correlation between independent variables.Solver