In multiple regression analysis, the square of the multiple correlation coefficient (R²) represents A) the amount of change that occurs in the dependent variable associated with each unit change in the independent variables. B) the joint reliability of the all the variables involved in the analysis. C) the proportion of variance in the dependent variables that can be accounted for by the independent variables considered as a set. D) the mean of the dependent variable.

Question

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The square of the multiple correlation coefficient (R²) represents the proportion of variance in the dependent variables that can be accounted for by the independent variables considered as a set. It is also known as the coefficient of determination and ranges from 0 to 1, with higher values indicating a stronger relationship between the variables. It is not directly related to the amount of change associated with unit changes in the independent variables or the reliability of the variables. It also does not represent the mean of the dependent variable.

In Multiple Regression Analysis, the Square of the Multiple Correlation