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During correlation analysis the relationship between the variables was assumed to be linear. Correlation analysis has its focal point of interest on measuring the strength of the linear associationship; it has no intention in finding the actual linear relationship between the variables. But in all practical purposes, we need to know the exact linear relationship; we want to know how the change in one variable affects the other variable(s). In nature, population characteristics are interrelated, and thereby change in one variable is associated with change in other variables also. As such unless and otherwise we know the relationship among the variables, it is very difficult to quantify the nature of changes in variables associated with the changes in other variables. Regression analysis facilitate in knowing the linear relationship among the variables.