In Multiple Linear Regression, we try to find the relationship between 2 or more independent variables (inputs) and the corresponding dependent variable (output). The independent variables can be continuous or categorical.
The equation that describes how the predicted values of y is related to p independent variables is called as Multiple Linear Regression equation :
Below is the graph for Multiple Linear Regression Model, applied on the iris data set:
Multiple linear regression analysis can help us in the following ways :
It helps us predict trends and future values. The multiple linear regression analysis can be used to get point estimates.
It can be used to forecast the effects or impacts of changes. That is, multiple linear regression analysis can help to understand how much will the dependent variable change when we change the independent variables.
It can be used to identify the strength of the effect that the independent variables have on a dependent variable.