A regression model expressing the dependent variable Y as a linear function of independent variable X is called a
Linear regression model. It is of the following form :
Y = α + βx + u
Where, Y = Dependent variable
X = Independent variable α,
β = Constants
u = Disturbance variable of model
Variable u shows the incompletness of Linear correlation between two variables X and Y.
- If there is perfect linear correlation between two variables X and Y, then the linear regression model is of the form
Y = α + β X. In such case the value of disturbance variable u will be 0 (zero).
- If there is partial linear correlation between two variables X and Y, the form of linear regression- model is
Y = α +βx + u.
