If recent momentum holds, Republicans would control both houses of Congress following midterm elections slated for November 4. With the possibility for a change in control of the Senate, we thought a timely call with Dr. Sam Wang, a Princeton professor and one of the most accurate political forecasters in the country, would be valuable. The call will cover Dr. Wang’s predictions for the election, critical factors driving the vote, and key races to watch. Dr. Sam Wang runs a meta-analysis model that incorporates the most recent polls from all 50 states and DC on a rolling basis. The model updates itself 4X daily, and while he prefers polls taken of likely voters rather than registered voters, but takes what’s made available everyday. His model provides a precise daily snapshot; he doesn’t predict outcomes, and the model nailed the 2012 elections, both the popular vote and the electoral college vote. As of yesterday afternoon, his model showed a Senate outcome of R-51, D-49. Seven Senate races are within one percentage point
Please join us TODAY, October 29th at 11 AM EDT: To pre-register, click on the link:
RenMac Conf Call: U.S. Midterm Elections Outlook with Sam Wang
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About Dr. Sam Wang & the Princeton Election Consortium:
Dr. Wang is an Associate Professor of Molecular Biology and Neuroscience at Princeton University. He is a best-selling author and recipient of multiple distinguished awards in his field. In addition to this work, in 2004 he created the Princeton Election Consortium to provide “meta-analysis” of state polls – a precise snapshot of where a race stands at any given point in time. His model also provides a prediction based on the current year’s polls and the amount of variation observed in similar past races.
How has it performed? In 2012, Dr. Wang’s model correctly predicted the winner of the presidential race, the Electoral College count, the popular vote share, and the winner of every single Senate race.
Dr. Wang received a B.S. in physics from Caltech and completed his doctorate in neuroscience at the Stanford University School of Medicine.