What are the assumptions of linear regression?

The main assumptions of linear regression are:
Linearity: The relationship between the independent and dependent variables is linear.
Independence: The residuals (errors) are independent.
Homoscedasticity: The variance of residuals is constant across all levels of the independent variable.
Normality: The residuals are normally distributed.