An Elections Officer Wants to Model Voter Turnout $( y )$

An elections officer wants to model voter turnout $( y )$ in a precinct as a function of the type of precinct.
Consider the model relating mean voter turnout, $E ( y )$ , to precinct type:
$$\begin{array} { l l } E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } , \text { where } & x _ { 1 } = 1 \text { if urban, } 0 \text { if not } \\& x _ { 2 } = 1 \text { if suburban, } 0 \text { if not } \\& \text { (Base level = rural) }\end{array}$$
The $p$ -value for the test $H _ { 0 } : \beta _ { 1 } = \beta _ { 2 } = 0$ is . 14 . Interpret the result.

A) Reject $H _ { 0 }$ at $\alpha = .10$ ; the model is useful for predicting voter turnout.
B) Reject $H _ { 0 }$ at $\alpha = .01$ ; there is evidence of a difference between the mean voter turnouts for urban, suburban, and rural precincts.
C) Reject the model since it only explains $14 \%$ of the variation.
D) Do not reject $H _ { 0 }$ at $\alpha = .10$ ; there is no evidence of a difference between the mean voter turnouts for urban, suburban, and rural precincts.