Difference between Correlation and Regression Analysis

1.Degree and Nature  of Relationship: Coefficient of correlation measures   the degree  of covariance  between two variables  whereas  the regression  analysis  tells  about  the nature  of relationship between the variable  so that one may be  able to estimate or predict the value of one variable  on the basis of another.

2. Cause and Effect Relationship: Correlation mearly  acertains the degree of relationship between two variables  and therefore one cannot  say that one variable  is the cause and other is the effect. In regression analysis one variable is taken as dependent variable while the other variable is taken as independent variable .Thus making it possible to study the cause and effect relationship.

3. The value of rx_y    in the calculation of coefficient of correlation measured the direction and degree of relationship between two variable say x and y. The values of   Ryx   Symmetric , it shows that it is immaterial which  of X   and Y  is dependent variable and which is independent variable. However in the case of regression analysis coefficients i.e.  by xy   are not symmetric i.e.   b _xy * b_yx   and therefore it certainly  makes a difference as to which variable  is dependent and which  one is independent.

4. In case of correlation, there may be nonsense correlation between two variables X and Y which  is due to merely chance and may not have any practical relevance, such as increase in income  and increase of environmental temperature. However there cannot be a nonsense regression. 

5. The value of coefficient of correlation is independent of changes of scale and point of origin. However regression coefficients are independent of changes of origin but not of scale.

6. While pointing out the difference between regression and correlation Werner z .Hirsch rightly stated that. While correlation analysis tests the closeness with which two phenomena co vary, regression analysis measured the nature and extent of the relation, that enabling us to make prediction.

Posted Date: 9/27/2012 6:24:40 AM | Location : United States

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