Why is the R2 is not a very good way to judge, if the specification of...
Why is the R2 is not a very good way to judge, if the specification of a multiple regression model has been improved by adding another variable?
Homework Answers
On adding a predictor to a model, the R-squared increases, even
if due to chance alone. It never decreases. Consequently, a model
with more terms may appear to have a better fit simply because it
has more terms.If a model has too many predictors and higher order
polynomials, it begins to model the random noise in the data. This
condition is known as overfitting the model and it produces
misleadingly high R-squared values and a lessened ability to make
predictions
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Why is the R2 is not a very good way to judge, if the
specification of...
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