= Solution
The three <Poisson regression> models have independent counts and a logarithmic <link function>: their mean predictors include both `pc` and `urban` in `m1`, only `urban` in `m2`, and only `pc` in `m3`. Nested comparisons through the full model are preferable to a direct comparison of the two nonnested one-predictor models.
To remove `urban` from `m1`, test $H_0:\beta_{\rm urban}=0$ against $H_1:\beta_{\rm urban}\ne0$. The <likelihood-ratio test> statistic is the deviance difference
$$
D_{m3}-D_{m1}=290.93-290.64=0.29,
$$
with approximate null distribution $\chi^2_1$. It is below $3.84$, so do not reject at 5%. The corresponding Wald <p-value> $0.588$ is consistent with this decision. To remove `pc` from `m1`, test $H_0:\beta_{\rm pc}=0$ against a nonzero coefficient, giving $559.17-290.64=268.53$ with approximate null distribution $\chi^2_1$; reject decisively. The <Akaike information criterion> also prefers `m3`, whose value $710.94$ is smaller than $712.65$ and $979.19$.
\b[Among these three models choose `m3`, retaining building cover and omitting the urban indicator.] This is a comparison within the stated Poisson family; its absolute fit must still be checked, as the next part does.
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