Tuesday’s election created lots of data about voting patterns in places that used different voting technologies. Various people have done exploratory data analysis, to see how jurisdictions that used e-voting might differ from those that did not. See, for example, the analysis cited in Joe Hall’s entry over at evoting-experts.com.
As a commenter on Joe’s entry (“Jon”) notes, voting technology is not the only difference between Florida counties that might account for the observed differences. Counties that used e-voting tend to be larger, more densely populated, and more Democratic-leaning than those that don’t. Perhaps these differences explain the data.
To answer questions like these would require more sophisticated data analysis, probably performed by a person who does such analyses for a living. Such a person could control for differences in voter demographics, for instance, to see whether there is an e-voting effect separate from the kinds of differences cited above. Such a person could also tell us how big the remaining effect is, and whether it is statistically significant.
It would be great if some hotshot social science data analyst would agree to do such a study. I’m sure that the folks out there who have data would be willing to furnish it, and to suggest theories to test.
It’s also worth thinking about what a particular finding would tell us. It’s one thing to find an anomaly in the data; but it’s another thing to explain what could have caused it. If you can point to an anomaly, but you don’t have a plausible story about how a rational election-stealing strategy would have caused that anomaly, then you don’t have strong proof of fraud, no matter how much evidence of the anomaly’s existence you can present.
If real anomalies exist, I think it’s more likely that they’ll turn out to be caused by errors or technology failures than by e-voting fraud. Either way, a careful study of the data might be able to teach us a lot about how well various voting technologies work in practice.
