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 ?
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2Correlation 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. – Michael R. Chernick Jun 03 '17 at 05:03