Define Linear Regression .

1.	Define Linear Regression .
Answer» 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.

Answer»

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.

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