All of the following are true, with the exception of one condition: A)a high R² or $\bar { R } ^ { 2 }$ does not mean that the regressors are a true cause of the dependent variable. B)a high R² or $\bar { R } ^ { 2 }$ does not mean that there is no omitted variable bias. C)a high R² or $\bar { R } ^ { 2 }$ always means that an added variable is statistically significant. D)a high R² or $\bar { R } ^ { 2 }$ does not necessarily mean that you have the most appropriate set of regressors.

Question

Quizplus · Accepted Answer

A high $R^2$ or adjusted $R^2$ ($\bar{R}^2$) does not guarantee that an added variable is statistically significant. $R^2$ measures the proportion of variance in the dependent variable that is predictable from the independent variables, but it does not directly indicate whether each individual regressor significantly contributes to the model. Statistical significance of individual regressors is typically assessed through t-tests or F-tests, not directly inferred from $R^2$ values.

All of the Following Are True, with the Exception of One