# Correlation and R-Squared

What is R2? In the context of predictive models (usually linear regression), where y is the true outcome, and f is the model’s prediction, the definition that I see most often is: In words, R2 is a measure of how much of the variance in y is explained by the model, f. Under “general conditions”, as Wikipedia says, R2 is also the square of the correlation (correlation written as a “p” or “rho”) between the actual and predicted outcomes: I prefer the “squared correlation” definition, as it gets more directly at what is usually my primary concern: prediction. If R2 … Continue reading Correlation and R-Squared