Four possible explanations why most of the polls got the US election wrong

In the US presidential election, the final poll of polls compiled by Real Clear Politics predicted that Hillary Clinton would win 46.8% of the popular vote and Donald Trump 43.6%. In the end, Clinton won 47.7% and her rival won 47.5%. This small majority she had in the popular vote was reversed in the electoral college and she won 228 delegates to Trump’s 279 (figures exclude New Hampshire, Arizona and Michigan). So the last-minute polls were accurate in predicting Clinton’s vote but were off by 4% in the case of the Trump vote. What went wrong?

Forecast error: presidential election polls and predictors

On Tuesday, 8 November 2016, the United States will hold its 58th quadrennial presidential election. Many pundits believe, as they have done throughout the campaign, that Democratic candidate Hillary Clinton stands a better chance of winning than Republican nominee Donald Trump. However, a new ABC News/Washington Post poll puts Trump ahead – albeit only by a percentage point, which is well within the poll’s margin of error.

The frequency of “America” in America

Official White House Photo by Chuck Kennedy
On what was a presumably cold January day in New York City in 1790, the first president of the United States of America, George Washington, gave a speech before a joint session of Congress. This speech, like those that have followed throughout history, is known as the State of the Union (SOTU) address.

Does Donald Trump “defy all odds”?

When FiveThirtyEight editor Nate Silver predicted in June that Donald Trump had a 20 per cent chance of winning the US presidential election against Hillary Clinton, eyebrows were raised. Just days before, experts had made a similar prediction about the chances of the British electorate voting to leave the European Union. Betting markets had the odds of a ‘Remain’ win as 4 to 1 in favour, and yet ‘Remain’ lost.

The EU referendum: surname diversity and voting patterns

An interesting by-product of the UK’s referendum on membership of the EU has been the wide variety of data analyses and visualisations to explain and add context, both before and after the results (for examples, see here, here and here). However, one of the few aspects that has not been analysed is how surname diversity in districts relates to referendum voting patterns.