What is the role of the 'R-squared' value in a multiple linear regression model?
- It represents the correlation between the dependent and independent variables
- It represents the error term in the regression model
- It represents the proportion of variance in the dependent variable that is predictable from the independent variables
- It represents the total variance in the dependent variable
The 'R-squared' value, also known as the coefficient of determination, in a multiple linear regression model represents the proportion of variance in the dependent variable that can be predicted from the independent variables. It ranges from 0 to 1, where a higher value indicates a better fit of the model.
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