Which two of the of the following statements are correct regarding R2 as a tool to evaluate a regression model. Multiple answers allowed.

Question

BlackTom AI · Accepted Answer

Option a: This statement is misleading because R-squared (R2) cannot exceed 1 in standard regression contexts. It represents the proportion of variance in the dependent variable that is explained by the model, and values greater than 1 indicate a mis-specified model or calculation error. In short, claiming R2 > 1 denotes a very good fit is incorrect.

Option b: Reporting R2 is common practice because it communicates how much of the variability in the outcome is explained by the model relative to a baseline. This helps users gauge the model’s precision and usefulness. This statement is correct.

Option c: The correct interpretation is that R2 is the proportion of the total variation in the dependent variable (Y) that can be explained by the variation in the model’s predictors (X), not the other way around. The phrasing here reverses the roles of X and Y, making this option incorrect.

Option d: R2 indeed reflects the model’s improvement over simply using the sample mean (Y-bar) as a predictor. It compares the residual variation under the model to the total variation around the mean, capturing how much better the model is at predicting Y than the mean alone. This statement is correct.

Which two of the of the following statements are correct regarding R2 as a tool to evaluate a regression model. Multiple answers allowed.多项选择题

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