What is the term for the correlation between the observed values of the outcome and the values predicted by a multiple regression model?

What is the term for the correlation between the observed values of the outcome and the values predicted by a multiple regression model?

• A. Multinomial logistic regression
• B. Multiple regression
• C. Multiple R
• D. Multivariate

Answer: (C)

The multiple correlation coefficient measures how closely a multiple regression model’s predictions match the actual outcomes. It is the correlation between the observed values of the dependent variable and the predicted values Ŷ produced by the regression model. This value, called Multiple R, captures the strength of the linear relationship between Y and Ŷ, and its square is R^2, the proportion of variance in Y explained by the predictors. The other terms refer to different concepts: a regression method that handles a categorical outcome (multinomial logistic regression), the overall technique of using several predictors (multiple regression), or analyses involving more than one dependent variable (multivariate).

The multiple correlation coefficient measures how closely a multiple regression model’s predictions match the actual outcomes. It is the correlation between the observed values of the dependent variable and the predicted values Ŷ produced by the regression model. This value, called Multiple R, captures the strength of the linear relationship between Y and Ŷ, and its square is R^2, the proportion of variance in Y explained by the predictors. The other terms refer to different concepts: a regression method that handles a categorical outcome (multinomial logistic regression), the overall technique of using several predictors (multiple regression), or analyses involving more than one dependent variable (multivariate).