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In the context of linear regression, R-squared (R²) is used to:
Determine the exact prediction errors.
Measure the difference between observed and predicted values for each point.
Check the multicollinearity between predictors.
Indicate the percentage of variance in the dependent variable explained by the independent variable(s)
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