Concept: Regression models can be evaluated using various loss metrics to measure their performance. One common metric, R² (coefficient of determination), represents the square of the correlation between x and y. This metric quantifies the amount of variance that the model-fitting procedure can effectively explain using the given data. Question: What value does R² normally produce to indicate the amount of variance explained in a regression model?