= Solution
Among all depth-one <regression tree> splits, the best split separates the second observation from the first and third by cutting advert1 between $0.89$ and $1.13$. The test point with advert1 equal to zero reaches the leaf containing responses $60$ and $53$, so the output is their <arithmetic mean>,
$$
\widehat y=\frac{60+53}{2}=56.5.
$$
This <decision stump> makes a piecewise-constant prediction far outside the observed predictor range and cannot extrapolate the spending trend towards the origin. Its shallow structure and leaf averaging keep its <variance of an estimator> modest, while that extrapolation failure can produce substantial <bias of an estimator>.
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