R² (coefficient of determination) measures the proportion of variance in the dependent variable that is predictable from the independent variable(s). R²=0.80 means 80% of variation in Y is explained by the model.
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R² always increases when adding more predictors — even random ones. Adjusted R² corrects for this by penalising model complexity.
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