What is the difference between R-squared and adjusted R-squared?
An example of an AI chatbot conversation about R-squared vs adjusted R-squared in statistics.
Can you explain the difference between R-squared and adjusted R-squared?
Sure! R-squared measures the proportion of variance in the dependent variable that's predictable from the independent variables.
What about adjusted R-squared? How is it different?
Adjusted R-squared adjusts the R-squared value based on the number of predictors in the model, preventing overfitting.
Why is adjusted R-squared considered better for model comparison?
It's better because it accounts for the number of predictors, providing a more accurate measure of model performance.
Can you give an example of when to use each?
Use R-squared for simple models, but prefer adjusted R-squared when comparing models with different numbers of predictors.
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