Simple linear regression model

Simple linear regression is a statistical method used to analyse the relationship between two variables: a dependent variable (which is the variable that is being predicted) and an independent variable (which is the variable that predicts the dependent variable). This type of regression uses a linear equation to model the relationship between the two variables. The equation for simple linear regression is y = mx + b, where y is the dependent variable, m is the slope of the line, x is the independent variable, and b is the y-intercept. The goal of linear regression is to determine the values of m and b that best describe the relationship between the two variables. This can be done by finding the line of best fit that minimizes the sum of squared errors between the predicted values and the actual values.