Oh, for the good ol’ days of political opinion polling — how innocent and straightforward it used to be. Even in the past five years it has changed beyond recognition.
Back then, it was still relatively straightforward: survey a group of people, usually between 1,000 and 2,000, ‘weight’ the answers to make them more representative of the whole UK population, and interpret the results. The methodological arguments that raged back then among the pointy-heads — telephone polls vs online polls; how to deal with past vote recall and turnout — have either now been settled or are at best secondary issues.
Polling companies were still, only half a decade ago, headed by larger-than-life public figures, more likely to have had a journalistic background than a statistical one, who regularly went on TV to “read the runes” for a grateful nation. For them, polling, like politics, was an art not a science.
Today, the question everyone asks during an election is still the same one — who is going to win? — but the world of opinion polling looks very different. We have, of course, all been burned by a succession of difficult elections with unexpected results that various polling companies failed to predict and as a result the media and public are rightly much more circumspect. We want to know more, before believing anyone’s predictions.
‘Data scientists’ are gradually replacing those grand ‘pollsters’ who used to offer confident insights with a neat turn of phrase. These new number nerds are likely to be under 30 and might well know nothing about politics. Instead of simple surveys and uniform national swings, they are using complex statistical models. For people whose bread and butter relies on being seen as a savvy political ‘expert’, all this amounts to an existential threat.
The most powerful data modelling technique in politics at the moment, is something called MRP. It stands for “multilevel regression with post-stratification” — not exactly catchy — and the number of people who fully understand it in the UK can be counted on two hands.
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