An elections officer wants to model voter turnout (y) in a precinct as a functio

Question

An elections officer wants to model voter turnout (y) in a precinct as a function of type of election, national or state. Write a model for mean voter turnout, E(y), as a function of type of election. A) E(y) = beta_ + beta_1 x_1 + beta_2 x_2, where x_1 = 1 if national, 0 if not and x_2 = 1 if state, 0 if not B) E(y) = beta_0 + beta_1 x, where x = 1 if national, 0 if state C) E(y) = beta_0 + beta_1 x + beta_2 x^2, where x = voter turnout D) E(y) = beta_0 + beta_1 x, where x = voter turnout Consider the model y = beta_0 + beta_1 x_1 + beta_2 x_2 + beta_3 x_3 + epsilon where x_1 is a quantitative variable and x_2 and x_3 are dummy variables describing a qualitative variable at three levels using the coding scheme x_2 = {1 if level 2 0 otherwise x_2 = {1 if level 3 0 otherwise The resulting least squares prediction equation is y = 16.3 + 2.3x_1 + 3.5x_2 + 1.8x_3 What is the response line (equation) for E(y) when x_2 = 0 and x_3 = 1? A) y = 16.3 + 2.3x_1 B) y = 16.3 + 4.1x_1 C) y = 18.6 + 2.3x_1 D) y = 18.1 + 2.3x_1

Explanation / Answer

37)

A. is not needed. As we don't flags separate for x1 and z2

B is right representation

C is wrong representation of linear reg, as it has higher powers of x ( x square)
therefore its not a linear regression equation

D is x is not voter turnout its type of election , so D is wrong

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