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# Regression and Lines of Regression Assignment Help

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Statistics - Regression and Lines of Regression

Statistics >> Regression and Lines of Regression

The concept of regression was first used by Sir Francis Galton in his study of heredity. The-general meaning of'Regressi9n' is to return or go back to the average value.

Regression indicates the average relationship between two variables and from this average relationship the average value of one variable is estimated corresponding to a given value of other variable. This process is known as simple regression. In regression analysis there are two types of variables-dependent variable and independent variable. A dependent variable is one whose value is to be predicted. It is also known as explained variable. An independent variable is the variable which influences the value of the other variable. It is- also known as explanator.

In the words of M.M. Blair, "Regression analysis is a mathematical measure of the average relationship between two or more variables in terms of the original units of the data."

**Lines of Regression **

Line of regression is the line which gives the best estimate of one variable for any specific value of the other variable. For bivariate distribution, we have two lines of regression.

(i) The regression line of Yon X - this gives the best estimated value of Y corresponding to a given value of X

(ii) The regression line of X on Y - This gives the best estimated values of X corresponding to a given value of Y.

There are always two lines of regression since each variable may be treated as the dependent as well as the independent variable. When we consider X as independent variable and Y as the dependent variable we get the regression line of Y on X Again, when we consider Y as independent variable and X as the dependent variable we get the regression line of X on Y.

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**Lines of Regression**

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