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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