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An Elections Officer Wants to Model Voter Turnout (Y) in a Precinct

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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: E(y)=β0+β1x1+β2x2E ( y ) = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } , where x1=1x _ { 1 } = 1 if urban, 0 if not
\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad x2=1x _ { 2 } = 1 if suburban, 0 if not
\quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad \quad (Base level == rural)

The pp -value for the test H0:β1=β2=0H _ { 0 } : \beta _ { 1 } = \beta _ { 2 } = 0 is .14. Interpret the restll.
A) Do not reject H0H _ { 0 } at α=.10\alpha = .10 ; there is no evidence of a difference between the mean voter turnouts for urban, suburban, and rural precincts.
B) Reject H0H _ { 0 } at α=.10\alpha = .10 ; the model is useful for predicting voter turnout.
C) Reject H0H _ { 0 } at α=.01\alpha = .01 ; there is evidence of a difference between the mean voter turnouts for urban, suburban, and rural precincts.
D) Reject the model since it only explains 14%14 \% of the variation.

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