medium · FRM Part 1
If an analyst reports that a regression's adjusted R^2 is negative, what is the most likely mathematical reason?
- The model has perfect multicollinearity, leading to an undefined adjusted R^2.
- The analyst has made an error, as adjusted R^2 is bounded between 0 and 1 just like raw R^2.
- The dependent variable has a negative correlation with all of the explanatory variables.
- The raw R^2 is very low, and the number of predictors (k) is high relative to the sample size (n).
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