1. One might expect that a respondent’s political ideology is likely to influence how that respondent feels about former Alaska governor, Sarah Palin. One might also suspect that a respondent’s gender has an influence on a respondent’s feelings towards Palin. It may also be the case that the effect of ideology on feelings about Sarah Palin is different for men than it is for women. Assume that ideology and gender are the only variables that affect the thermometer score that a respondent assigns to Sarah Palin, and that ideology and gender may have an interactive effect. Using the 2008 NAES data and your preferred software package(s), do the following.

1. State your expectations regarding the signs that you would expect to see on the coefficients on ideology, gender, and the interaction term in a regression of feelings towards Sarah Palin on those three variables. (You should also state why you have these expectations).
2. Run the regression
3. Interpret your results (Note: If you answer D, E, F, or G in completing C, you needn’t repeat yourself.)
4. Are the intercepts the same for men and women? What do the intercepts indicate in a
   substantive sense?
5. What is the difference in predicted thermometer scores between men and women among the most conservative respondents?
6. What is the difference in predicted thermometer scores between men and women among the most liberal respondents?
7. Is the effect of ideology the same for men as it is for women?

(2) (A) Using Excel, generate a 3D graph of the following regression equation:

(B) Based on the graph, (roughly) describe how the effect of \({{X}_{1}}\) on \(\hat{Y}\) when X ₂ = 0 differs from the effect of \({{X}_{1}}\) on \(\hat{Y}\) when X ₂ = 10.

(C) What is the precise effect of a one-unit increase in X ₂ on \(\hat{Y}\) when X ₁ = 0? What is the precise effect of a one-unit increase in X ₂ on \(\hat{Y}\) when X ₁ = 7?

(3) To the best of your ability, use the 2008 NAES data to replicate Model 1 in Table 1 of Diana Mutz’s 2010 paper in PS, "The Dog that Didn’t Bark: The Role of Canines in the 2008 Campaign." Present your results in a nice table. Also turn in frequency tables of all the variables you use in your final model. Run visual and/or analytical tests of each of the Gauss- Markov assumptions and describe the results of these tests.

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