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The dictionary meaning of the term 'regression' is the act of returning or going back. The term was first used by Sir Francis Galton in 1877 when he analyzed the relationship between the height of fathers and sons.

His study of the heights of fathers and sons revealed a very interesting relationship-tall fathers tend to have tall sons and short fathers, short sons, but the average height of the son of a group of tall fathers is less than that of the fathers and the average height of the sons of short fathers is greater than that of the fathers. The line describing this tendency to regress or step back was called by Galton a Regression Line. The term continues to be in use to represent the trend present but no longer has it necessarily carried the original implication of stepping back that Galton intended.

The statistical device that enables the estimation or prediction of the unknown values of one variable based on the known values of another variable is termed regression. Regression is the measure of average relationship between variables.

Linear Regression

In case there exists relationship between two variables x and y the plotted points in the scatter diagram lie concentrated around a curve and the relationship is said to be expressed by means of curvilinear regression. In the particular case, when the curve is a straight line, is called the line of regression and the regression is said to be linear. Once it is known that the relationship is expressible by means of straight line, a technique known as the Principles of Least Squares is adopted to fit the line on the basis of the given bivariate data.

A line of regression gives the most probable values of one variable for the given value of the other variable. For two series x and y there are two regression lines, one on assuming x as dependent and y dependent variable and the two on assuming x as dependent and independent variable.

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