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If you've ever wondered how two or more things relate to each other, or if you've ever had your boss ask you to create a forecast or analyze relationships between variables, then regression is the solution.
The correlation calculation simply takes the covariance and divides it by the product of the standard deviation of the two variables. This will bound the correlation between a value of -1 and +1. A correlation of +1 can be interpreted to suggest that both variables move perfectly positively with each other, and a -1 implies they are perfectly negatively correlated.Now that we know how the relative relationship between the two variables is calculated, we can develop a regression equation to forecast or predict the variable we desire, The regression equation simply describes the relationship between the dependent variable (y) and the independent variable (x).
Regression is the right tool when you want to see the relatiionship between two or more things somehow related to each other like hight and weight for a random sample of20 male students in James High School.
The correlation simply show the level of variance in response between two or more variables and how sensitive they are to each other. The calculation for the correlation does not get higher than1 which means they move in the same direction and never less than -1 which means they move in the oppsite direction completly.0 value means that there is no relationship at all. For example, there is no relationship between ability of driving an airplane and drinking milk in the morning. The correlation value in the previous example will be0.
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