Which of the following correctly describes the coefficient of multiple determination?
A) It is denoted byand is interpreted as the proportion of the total variation that is explained by the regression of y on the predictor variables.
B) It is computed as the ratio of total variation to explained variation.
C) In the case of two independent variables, it describes how well the regression hyperplane fits the data.
D) It is computed as the ratio of total variation to explained variation and in the case of two independent variables, it describes how well the regression hyperplane fits the data.
E) None of these.

Question

Quizplus · Accepted Answer

The coefficient of multiple determination (R-squared) is denoted by and represents the proportion of the variance in the dependent variable (y) that is explained by the independent variables (predictors) in the regression model. Choice B is incorrect as it falsely implies that the ratio of total variation to explained variation is the coefficient of determination, which is the square of the correlation coefficient. Choice C is incorrect as it is only applicable to two independent variables and disregards the other cases. Choice D combines the incorrect statement from option B with the limitation of option C.

Which of the Following Correctly Describes the Coefficient of Multiple