Linear Regression

Linear regression is a mathematical model that describes the relationship between two or more variables. In statistics, linear regression is used to predict the value of a dependent variable (y) based on the value of an independent variable (x). The linear regression equation is: y = β0 + β1x where β0 is the intercept and β1 is the slope.

The linear regression model makes several assumptions about the data:

The dependent variable is a linear function of the independent variable.

There is no interaction between the independent variables.

There is no multicollinearity between the independent variables.

The error term is normally distributed with a mean of zero.