Here at FiveThirtyEight, we’ve been skeptical of claims of irregularities in the presidential election. As we pointed out last week, there are no obvious statistical anomalies in the results in swing states based on the type of voting technology that each county employed. Instead, demographic differences, particularly the education levels […] Read more »
Some thoughts about the reports of supposed evidence of election irregularities in MI, PA, and WI
The Internet lit up on Monday over the news, reported in New York Magazine, that a team of computer scientists and lawyers had reported to the Clinton campaign that “they’ve found persuasive evidence that results in Wisconsin, Michigan, and Pennsylvania may have been manipulated or hacked.” … Many of my […] Read more »
How Millennials voted this election
… While many expected the low favorability ratings of the two candidates and the divisiveness of this election year to keep young voters home, 2016 saw similar rates of young adult turnout as 2012. On election day, Hillary Clinton won the youth vote (55 percent) while Donald Trump only garnered […] Read more »
Education, Not Income, Predicted Who Would Vote For Trump
Sometimes statistical analysis is tricky, and sometimes a finding just jumps off the page. Here’s one example of the latter. I took a list of all 981 U.S. counties with 50,000 or more people and sorted it by the share of the population that had completed at least a four-year […] Read more »
The presidential election: Illness as indicator
… The Institute for Health Metrics and Evaluation at the University of Washington has compiled county-level data on life expectancy and the prevalence of obesity, diabetes, heavy drinking and regular physical activity (or lack thereof). Together, these variables explain 43% of Mr Trump’s gains over Mr Romney, just edging out […] Read more »
The county-by-county data on Trump voters shows why he won
In trying to explain Donald Trump’s stunning victory last week, observers have offered numerous explanations. … One way of testing various explanations against one another is to examine county-level vote returns, where contextual information — education levels, racial composition and so forth — can help sort out statistically which factors […] Read more »