Respuesta :
Answer:
C
Explanation:
Adjusted R^2 is calculated for multiple explanatory variables and R^2 value is calculated for only one explanatory variable.
Adjusted R^2 is always greater than R^2. As the sample size is increased or more variables are included, R^2 value increases and becomes closer to adjusted R^2 value. Adjusted R^2 value accounts for the number of variables and sample size
It is better to use values of adjusted Rsquared instead of simply using values of R² because C. The unadjusted R² increases or remains the same as more variables are included, but the adjusted R² is adjusted for the number of variables and sample size.
It should be noted that R² simply means that every time a predictor is added to a model, this will lead to an increase in the R-squared even if it's as a result of a chance.
The adjusted R² is the modified version of R squared that has been adjusted for the number of predictors that are in the model. It is better to use values of adjusted Rsquared because the adjusted R² is adjusted for the number of variables and sample size.
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