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Correlation and regression are statistical measurements that are used to quantify the strength of the linear relationship between two variables. Correlation determines if there is a relationship, while regression quantifies that relationship.

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Final answer:

Correlation and regression are statistical measurements used to quantify the strength of the linear relationship between two variables. Correlation determines if there is a relationship, while regression quantifies that relationship. The correlation coefficient, represented by the letter r, is a number from -1 to +1 that indicates the strength and direction of the relationship between variables.

Step-by-step explanation:

Correlation and regression are statistical measurements used to quantify the strength of the linear relationship between two variables. Correlation determines if there is a relationship, while regression quantifies that relationship. The correlation coefficient, represented by the letter r, is a number from -1 to +1 that indicates the strength and direction of the relationship between variables. Regression analysis is a more complex technique that helps determine the strength and direction of causality between a dependent variable and one or more independent variables. It allows for better analysis of the effect of multiple variables on the dependent variable.

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