This blog’s mission is to provide informed analysis of US national elections by members of the Princeton academic community. It is open to scholars in the Princeton area from all disciplines, including (but not restricted to) politics, neuroscience, psychology, computer science, and mathematics.
For now, much of the site’s information is about polling. As the campaign season progresses we will expand to other interesting topics, and expect for diverse contributions. To write for us, please contact Sam Wang.
This blog began in 2004 as a meta-analysis directed at the question of who would win the Electoral College. Meta-analysis of state polls provides more objectivity and precision than looking at a single poll and gives an accurate current snapshot of the state of play. Over the course of the campaign, this site attracted over a million visits. In 2004, the median decided-voter calculation on Election Eve captured the exact final outcome (read this article and the follow-up). The 2008 calculation provided results based on decided-voter polling from all 50 states, and in the closing week of the campaign ended up within 1 electoral vote of the final outcome.
Prof. Sam Wang‘s academic specialties are biophysics and neuroscience. In these fields he uses probability and statistics to analyze complex experimental data, and has published many papers using these approaches. He is also the author of Welcome To Your Brain, a popular book about his field.
He originally developed the Meta-Analysis in 2004 to help think about how to allocate campaign contributions. He was originally motivated by the fact that in a close race, one can make the biggest difference by donating at the margin, where probabilities for success are 20-80%. The Meta-Analysis has subsequently been found to be useful as a highly sensitive tracking tool over time. To read a discussion click here. In 2004, the Meta-Analysis of State Polls got tens of thousands of hits per day. He was helped that year by Drew Thaler. Sam can be contacted as sswang at princeton dot edu.
Andrew Ferguson is a 2008 Princeton graduate and responsible for the site’s data processing and infrastructure. While in college, he studied probability, statistics, and computer science. He is currently a computer science graduate student at Brown University, where he works on Software Defined Networks and frameworks for analyzing Big Data.