Coefficient of determination

Summary

The coefficient of determination, written $R^2$, measures how much of the variation of a response is explained by a fitted regression model. It compares the residual sum of squares with the total sum of squares around the mean. For ordinary least squares with an intercept, it lies between $0$ and $1$ and equals the squared correlation between the observed and the fitted values. It is the most common summary of goodness of fit in linear regression.