10.) Please provide necessary work with answers:

a.) There is some evidence that political views are shaped by where one grew upin a city, in a suburb, or in a rural area. Using the comm variable (0 = rural; 1 = suburban; 2 = urban), we run a regression explaining where one lies along the pro/anti death penalty spectrum (0 = anti death penalty, 4 = pro death penalty). Using the results below, assess that relationship. What is the null hypothesis (be specific)? Do we reject it or not? Interpret your findings for the layperson as well.

. regress deathpen comm

Source | SS df MS Number of obs = 167

-------------+------------------------------ F( 1, 165) = 1.35

Model | 3.05782443 1 3.05782443 Prob > F = 0.2462

Residual | 372.570918 165 2.25800556 R-squared = 0.0081

-------------+------------------------------ Adj R-squared = 0.0021

Total | 375.628743 166 2.26282375 Root MSE = 1.5027

------------------------------------------------------------------------------

deathpen | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

comm | -.1873282 .1609754 -1.16 0.246 -.5051653 .1305089

_cons | 2.646921 .1893246 13.98 0.000 2.27311 3.020733

------------------------------------------------------------------------------

b.) Our comm variable is nice, but its not really a ratio level variable and thus really shouldnt be used in a regression format in such as manner. Instead, we decide to use a dummy variable approach. The variables urban, rural, and suburban are each dichotomous variables that indicate whether the respondent is either in or not in those respective categories. We decide to use suburban (48%) as the reference category. In considering the following results, what more have we learned about the relationship between locale and support for the death penalty? Interpret the findings in terms of the null hypotheses and for the layperson.

. regress deathpen urban rural

Source | SS df MS Number of obs = 167

-------------+------------------------------ F( 2, 164) = 2.60

Model | 11.5261975 2 5.76309877 Prob > F = 0.0776

Residual | 364.102545 164 2.22013747 R-squared = 0.0307

-------------+------------------------------ Adj R-squared = 0.0189

Total | 375.628743 166 2.26282375 Root MSE = 1.49

------------------------------------------------------------------------------

deathpen | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

urban | -.6698867 .2941559 -2.28 0.024 -1.250708 -.0890658

rural | -.2362025 .2692689 -0.88 0.382 -.7678833 .2954783

_cons | 2.696203 .1676395 16.08 0.000 2.365193 3.027213

------------------------------------------------------------------------------

c.)

We run one last regression on the death penalty, including only the dummy variable for rural locale. What is our reference group in this case? Explain the results. Given the three relationships weve explored here in these three regressions, what do think is going on here? Whats the best way to express the statistical relationship between support for abortion rights and where one grew up?

. regress deathpen urban

Source | SS df MS Number of obs = 167

-------------+------------------------------ F( 1, 165) = 4.43

Model | 9.817849 1 9.817849 Prob > F = 0.0369

Residual | 365.810894 165 2.21703572 R-squared = 0.0261

-------------+------------------------------ Adj R-squared = 0.0202

Total | 375.628743 166 2.26282375 Root MSE = 1.489

------------------------------------------------------------------------------

deathpen | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

urban | -.5783354 .2748261 -2.10 0.037 -1.120965 -.0357062

_cons | 2.604651 .1310966 19.87 0.000 2.345808 2.863494

------------------------------------------------------------------