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) There is some evidence that political views are shaped by where one grew upin a city, in a suburb, or in a rural area.
10.)
a.) There is some evidence that political views are shaped by where one grew up—in 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 abortion spectrum (0 = pro-life, 4 = pro-choice). 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 abort comm
Source | SS df MS Number of obs = 305
-------------+---------------------------------- F(1, 303) = 2.57
Model | 5.36960305 1 5.36960305 Prob > F = 0.1100
Residual | 633.364823 303 2.09031295 R-squared = 0.0084
-------------+---------------------------------- Adj R-squared = 0.0051
Total | 638.734426 304 2.10110009 Root MSE = 1.4458
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abort | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
comm | .1886133 .1176811 1.60 0.110 -.0429625 .420189
_cons | 2.79301 .1382604 20.20 0.000 2.520938 3.065082
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b.) Our "comm" variable is nice and ordinal, but it's not really a ratio level variable and thus really shouldn't 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 (50%) as the reference category. In considering the following results, what more have we learned about the relationship between locale and support for abortion? Explain what our dummy variable approach tells us. Interpret the findings in terms of the null hypotheses and for the layperson.
. regress abort rural urban
Source | SS df MS Number of obs = 305
-------------+---------------------------------- F(2, 302) = 2.18
Model | 9.10274152 2 4.55137076 Prob > F = 0.1145
Residual | 629.631685 302 2.08487313 R-squared = 0.0143
-------------+---------------------------------- Adj R-squared = 0.0077
Total | 638.734426 304 2.10110009 Root MSE = 1.4439
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abort | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
rural | -.3973856 .1953319 -2.03 0.043 -.7817695 -.0130017
urban | -.0467271 .2115281 -0.22 0.825 -.4629827 .3695284
_cons | 3.091503 .1167331 26.48 0.000 2.86179 3.321217
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c.) We run one last regression on abortion politics, including only the dummy variable for rural locale. What is our reference group in this case? Explain the results. Given the three relationships we've explored here in these three regressions, what do think is going on here? What's the best way to express the statistical relationship between support for abortion rights and where one grew up?
. regress abort rural
Source | SS df MS Number of obs = 305
-------------+---------------------------------- F(1, 303) = 4.33
Model | 9.00100377 1 9.00100377 Prob > F = 0.0383
Residual | 629.733422 303 2.07832813 R-squared = 0.0141
-------------+---------------------------------- Adj R-squared = 0.0108
Total | 638.734426 304 2.10110009 Root MSE = 1.4416
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abort | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
rural | -.3831551 .1841137 -2.08 0.038 -.7454585 -.0208516
_cons | 3.077273 .0971954 31.66 0.000 2.886009 3.268536
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