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.

Question

Quizplus · Accepted Answer

The coefficient of multiple determination (R-squared) is denoted by R-sq and represents the proportion of the total variation in the dependent variable (y) that is explained by the regression model with one or more predictor variables. It ranges from 0 to 1, where R-sq=0 indicates that the model explains none of the variation, whereas R-sq=1 indicates that the model explains all of the variation in the dependent variable. Therefore, choice A correctly describes the coefficient of multiple determination. Choice B describes the F-statistic, which is used to test the overall significance of the regression model. Choice C describes the coefficient of determination in the case of two independent variables, which is equivalent to R-sq.

Which of the Following Correctly Describes the Coefficient of Multiple