GROUP NO-8

BHAVI SHAH

ROLL NO-2013007

Linear regression models are often fitted using the least squares approach,

Linear regression analysis is a technique used for predicting the unknown value of a variable from the known value of another variable

More efficiency  if X and Y are two related variables  then linear regression analysis helps us to imagine the value of Y for a given value of X or imagine the value of x for a given value of y

For example age of a human being and maturity are related variables. Then linear regression analyses can predict level of maturity given age of a human being.

The linear regression is based on two variable dependent and independent

Dependent variable-The variable whose value is to be predicted is known as the dependent variable

Independent variable-the one whose known value is used for prediction is known as the independent variable

THERE ARE TWO LINE OF REGRESSION

Y ON X and X ON Y

The line of regression of Y on X is given by Y = a + Bx   this is used to know the unknown value of variable Y when value of variable X is known.

The line of regression of X on Y is given by X = c + Dy  which is used to predict the unknown value of variable X using the known value of variable Y.

Linear regression does not test whether data is linear. It finds the slope and the intercept relation between the independent and dependent variable can be best explained by a straight line.