Multiple Linear Regression:
A linear regression model with more than one predictor variable is called multiple linear regression. In multiple linear regression, we have one dependent variable and multiple dependent variables. That dependent variable is what we are trying to predict. The main motto of this model is to identify the relationship between dependent variables and independent variables.
The Equation for Multiple Linear Regression:
Y=β0+β1X1+β2X2+…+βpXp+ε
Today’s class professor gave an example of multiple linear regression, in which Y is the dependent variable. And X1, X2 are the independent variables, and Y is for diabetes, X1 for inactivity, and X2 for obesity.
OVERFIT:
The model is a very good (ever perfect) fit to the data but behaves poorly with new data.