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# Difference Between Correlation and Regression

Correlation indicates only the nature and extent of linear relationship. Regression is the study about the impact of the independent variable on the dependent variable. It is used for predictions.

DIFFERENCE BETWEEN CORRELATION AND REGRESSION ## Correlation

1. It indicates only the nature and extent of linear relationship

2. If the linear correlation is coefficient is positive / negative , then the two variables are positively / or negatively correlated

3. One of the variables can be taken as x and the other one can be taken as the variable y.

4. It is symmetric in x and y,

ie., rXY = rYX

## Regression

1. It is the study about the impact of the independent variable on the dependent variable. It is used for predictions.

2. The regression coefficient is positive, then for every unit increase in x, the corresponding average increase in y is bYX. Similarly, if the regression coefficient is negative , then for every unit increase in x, the corresponding average decrease in y is bYX.

3. Care must be taken for the choice of independent variable and dependent variable. We can not assign arbitrarily x as independent variable and y as dependent variable.

4. It is not symmetric in x and y, that is, bXY and bYX  have different meaning and interpretations.

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12th Statistics : Chapter 5 : Regression Analysis : Difference Between Correlation and Regression |