Multiple Linear Regression
Multiple linear regression is used to estimate the relationship between two or more independent variables and one dependent variable.
Example-The selling price of a house can depend on the desirability of the location, the number of bedrooms, the number of bathrooms, the year the house was built, the square footage of the lot and a number of other factors.
Here
Dependents variable ->
Selling price of a house
Independent variable->
Location, Number of bathrooms , year the house build, square footage and other factors
The Formula for Multiple Linear Regression Is
yi = β0 + β1xi1 + β2xi2 + ... + βpxip + ϵ
where, for i=n observations:
yi = dependent variable
xi = expanatory variables
β0 = y-intercept (constant term)
βp = slope coefficients for each explanatory variable
ϵ = the model’s error term (also known as the residuals)