= Solution
The intercept-only model has $49$ residual degrees of freedom, so the sample size is $50$. The one-covariate model and full model therefore have respectively $48$ and $47$ residual degrees of freedom. The completed sequential <analysis of variance> table has
$$
\begin{array}{c|c|c|c|c|c}
&\mathrm{Res.Df}&\mathrm{RSS}&\mathrm{Df}&\mathrm{Sum\ of\ Sq}&F\\ \hline
1&49&164.448&&&\\
2&48&30.831&1&164.448-30.831&\dfrac{164.448-30.831}{30.817/47}\\
3&47&30.817&1&30.831-30.817&\dfrac{30.831-30.817}{30.817/47}
\end{array}
$$
Thus the missing sums of squares are $133.617$ and $0.014$, and the corresponding <F-statistic>[F-statistics] are approximately $203.8$ and $0.0214$. The first p-value is below $2\times10^{-16}$; the second is approximately $0.8845$. The tiny second increment is consistent with the reported <Student's t-test>[t-test] because, for one added coefficient, the partial F-statistic equals the squared t-statistic up to displayed rounding.
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