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How does linear regression differ from multiple regression?
a. Linear regression is a statistical technique using a regression equation to determine the "line of best fit" from which a Y score can be predicted from an X score. Multiple regression has the same goal as linear regression, but uses two or more independent variables rather than one independent variable.
b. Linear regression has two or more independent variables rather than one independent variable (which is what is used in linear regression). Multiple regression is a statistical technique using a regression equation to determine the "line of best fit" from which a Y score can be predicted from one independent variable.
c. There is no difference between the two regressions.
d. Linear regression is a statistical technique using a regression equation to determine the "line of best fit" from which a Y score can be predicted from itself. Multiple regression has the same goal as linear regression, but uses only one independent variable.
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