I am learning Statistics as a prerequisite for Data Science course. I would like to know the difference between Correlation and Regression with an example.

Could someone help me please ?


marked as duplicate by kjetil b halvorsen, Michael Chernick, mdewey, jpmuc, gung Jun 15 '17 at 13:09

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    $\begingroup$ Correlation measures the tendency for a variable say Y to increase as another variable X increases (positive correlation) or decrease as X increases (negative correlation). Simple linear regression estimates the Expected value of Y given X=x for various values of x. The estimated slope of the regression function is directly proportional to the Pearson sample product moment correlation coefficient. When considering correlation the order of the variables X and Y doesn't matter. When doing regression it does. As I describe it, Y is the dependent variable and X is the independent variable. $\endgroup$ – Michael Chernick Jun 3 '17 at 5:03

Correlation tells magnitude of relatioship or association irrespective of the association being positive or negative. The regression analysis) indicates the average change in Y (absolute value) following changes in the X variable.The regression coefficient b indicates rate of change in X. Thus correlation is a ratio estimate and regression analysis predicts Y for a given X. The two are not a similar measure.


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