Difference between Correlation and Regression:
Correlation:
1. Correlation is the relationship between two or more variables, which vary with the other in the same or the opposite direction.
2. Both the variables X and Y are random variables.
3. It finds out the degree of relationship between two variables and not the cause and effect relationship.
4. It is used for testing and verifying the relation between two variables and gives limited information.
5. The coefficient of correlation is a relative measure. The range of relationship lies between -1 and +1.
6. There may be spurious correlation between two variables.
7. It has limited application, because it is confined only to linear relationship between the variables.
8. It is not very useful for further mathematical treatment.
Regression:
1. Regression means going back and it is a mathematical measure showing the average relationship between two variables.
2. Both the variables may be random variables.
3. It indicates the cause and effect relationship between the variables and establishes functional relationship.
4. Besides verification it is used for the prediction of one value, in relation to the other given value.
5. Regression coefficient is an absolute figure. If we know the value of the independent variable, we can find the value of the dependent variable.
6. In regression there is no such spurious regression.
7. It has wider application, as it studies linear and nonlinear relationship between the variables.
8. It is widely used for further mathematical treatment.
