Section 13.2 Analyzing Voting for Romney
Let’s move onto running a regression for the second category of our dependent variable:
. reg vote_2 race_2 race_3 race_4 race_5 race_6
Source | SS df MS Number of obs = 3,036
-------------+---------------------------------- F(5, 3030) = 72.35
Model | 78.6117037 5 15.7223407 Prob > F = 0.0000
Residual | 658.463395 3,030 .217314652 R-squared = 0.1067
-------------+---------------------------------- Adj R-squared = 0.1052
Total | 737.075099 3,035 .242858352 Root MSE = .46617
------------------------------------------------------------------------------
vote_2 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
race_2 | -.483031 .0280207 -17.24 0.000 -.5379725 -.4280895
race_3 | -.2002027 .0540143 -3.71 0.000 -.306111 -.0942944
race_4 | -.0822373 .1349253 -0.61 0.542 -.3467917 .182317
race_5 | -.3014791 .0320617 -9.40 0.000 -.364344 -.2386142
race_6 | -.1344972 .0440105 -3.06 0.002 -.2207906 -.0482038
_cons | .498904 .0097607 51.11 0.000 .4797657 .5180423
Now we’re looking at predictions of voting for Mitt Romney. Our constant is .50, indicating that a non-Hispanic White voter has a 50% chance of voting for Mitt Romney. The coefficient of -.48 for race_2 indicates that (non-Hispanic) Black voters are 48 percentage points less likely to vote for Mitt Romney than (non-Hispanic) White voters. I won’t go on to interpret the rest of the coefficients, but they follow the same pattern.
