My daughter Carrie, a junior at University of Minnesota — majoring in political science, asked me to look over a paper she wrote last week for her quantitative-analysis class. Her assignment was to test “the theory that Christian religiosity, measured through church attendance, affected the outcome of the 2004 presidential election” (Bush over Kerry). Carrie considered many other variables that could logically have influenced voting decisions before settling on two alternative factors – per-capita income, and level of education.
As I’d expected, her regression analysis (using the SPSS software) showed a positive correlation of “frequent church goers” voting for Bush (0.166 R2) and negative for “population with college degree or higher” (0.293). However, the highest correlation was seen with per-capita income, which surprised me by being negative – the more the voter earned, the more likely they were to NOT vote for Bush. I always thought that the Republicans were the party of the rich. But from this data one must conclude that they mainly appeal to poor, less-educated church-goers! (Please do not take the previous two ‘tongue-in-cheek’ statements seriously, I am only making a humorous point about how misleading statistics can be!)
I don’t give too much credence to any of this – mainly due to my great skepticism of using statistics to dissect historical data and generate inferences on cause and effect relationships. However, it makes me curious as to the driving forces of today’s party politics in the USA. That’s about all I figure that regression of happenstance data really offers – some food for thought that may lead to more rigorous investigation.