Data Science Simplified Part 4: Simple Linear Regression Models

Linear regression models are not perfect. It tries to approximate the relationship between dependent and independent variables in a straight line. Some errors can be reduced. Some errors are inherent in the nature of the problem. These errors cannot be eliminated. They are called as an irreducible error, the noise term in the true relationship that cannot fundamentally be reduced by any model.