= Coefficient of determination
{title2=$R^2$}
{wiki}
= R squared
{c}
{synonym}
In an <ordinary least squares> regression with an intercept and a nonconstant response, $R^2=1-\mathrm{RSS}/\sum_i(Y_i-\overline Y)^2$. It measures the fitted proportion of sample variation relative to an intercept-only baseline. It increases when regressors are added, even if those regressors are unhelpful for prediction. A high value does not establish the assumptions of a <normal linear model> or rule out a systematic <regression residual> pattern.
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