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# REGRESSION - Correlation And Regression Analysis

Posted On :  26.05.2018 10:04 pm

In the pairs of observations, if there is a cause and effect relationship between the variables X and Y, then the average relationship between these two variables is called regression, which means “stepping back” or “return to the average”.

REGRESSION

In the pairs of observations, if there is a cause and effect relationship between the variables X and Y, then the average relationship between these two variables is called regression, which means “stepping back” or “return to the average”. The linear relationship giving the best mean value of a variable corresponding to the other variable is called a regression line or line of the best fit. The regression of X on Y is different from the regression of Y on X. Thus, there are two equations of regression and the two regression lines are given as follows:

Result:

Let σx, σy denote the standard deviations of x, y respectively. We have the following result.

Result:

The coefficient of correlation r between X and Y is the square root of the product of the b values in the two regression equations. We can find r by this way also.

Application

The method of regression is very much useful for business forecasting.
Tags : Research Methodology - Correlation And Regression Analysis
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