Drew Linzer: The stats man who predicted Obama’s win

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Pundits insisted the presidential race was a toss-up, but "polling aggregators" were being criticised for favouring President Obama.

Pundits insisted the presidential race was a toss-up, but “polling aggregators” – who analyse polls to make predictions – were being criticised for favouring President Obama.

Report by BBC.co.uk

Not any more.

In September we called Drew Linzer, an associated professor of political science at Emory University, to ask for his predictions for the upcoming US presidential election.

Linzer runs the website Votamatic, which uses current election polls and past historical trends to predict the outcome of major elections. He gave the same prediction he had been posting on his site since 23 June.

Obama 332 votes, Romney 206.

Weeks later, the first presidential debate, when Obama’s lacklustre performance kicked off a surge of momentum for the Republican challenger Mitt Romney, Obama’s election odds had sunk like a stone in national polls, and states once considered toss-ups were being assigned as favourites for Romney.

Asked again for his updated prediction, Linzer gave the same answer.

No change, he said: Obama 332 votes, Romney 206.

Now, Obama has been elected to a second term, and election workers are still counting the votes in Florida, which is leaning ever so slightly towards the Democrats. The Romney team admitted to the Miami Herald that they had lost the state, though it has not been officially called. When it is, the final tally in this once too-close-to call election will be:

Obama, 332 votes, Romney 206.

Aside from Barack Obama himself it is people such as Linzer – along with his contemporaries Nate Silver, who writes the Five Thirty Eight blog at the New York Times, and Sam Wang, co-founder of the Princeton Election – who may be this November’s big winners.

In a race that many old-school pundits said was too close to call, Linzer, Silver and Wang, who all run websites that use some version of voter aggregation and statistical analysis to predict elections, had Obama as a clear favourite with a slim but persistent lead.

“We really shouldn’t be all that surprised that our methods ‘worked’ on election day,” says Linzer.

“All this proves is that public opinion research is still a reliable and accurate way to learn about people’s voting preferences… as we’ve known all along. [There’s] no need to go on gut instincts or intuition or whatever else the pundits are doing, when we have actual real information,” says Linzer.

But those who built their living on gut instinct and intuition were surprised. For weeks, journalists and pollsters were convinced that the work of Linzer, Silver and Wang was politically biased or that their maths was wrong.

These men and their statistical models have now been proven correct – and that means re-evaluating what we think we know about politics, polling, and how to win the presidency.

‘Ideologues’?

These aggregators are based on a simple premise.

“Pollsters individually make mistakes, no matter how well-constructed their polls are, but in the aggregate they are quite sound,” says Sam Wang, who in his day job is an associate professor of molecular biology and neuroscience at Princeton University.

And in the past two election cycles, the number of state polls being conducted – along with an advance in computing technology – has allowed those polls to be aggregated, weighted and indexed to produce a clear probability of how people will vote.

Each of the aggregating websites uses a slightly different formula to come to their results, whether it’s looking at historical trends or including economic data and other outside factors to temper the result on voters. But in 2012, all of the websites ran thousands of models predicting a probable win for Barack Obama.

“The polling this year has been remarkably stable,” says Linzer, and even though it dipped after Obama’s disastrous debate performance, it wasn’t enough to radically shake the aggregate predictions – even though individual polls might be fluctuating.

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