= Solution
\b[TODO: the model's explained-variance value is absent.] For an ordinary least-squares <linear regression> with an <intercept>, the <coefficient of determination> is $R^2=1-SS_{\mathrm{residual}}/SS_{\mathrm{total}}$. Its value multiplied by one hundred is the corresponding percentage of sample variation explained by that fitted model. Read the actual reported $R^2$ and distinguish it from the <adjusted coefficient of determination>; neither is a verified prediction-performance estimate on new data. Without the missing summary or sums of squares, no numerical percentage can be recovered.
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