Evaluating the significance of a survey used to be fairly straightforward – for any truly random sample, there is a well-defined margin of error which allows a critical reader to judge how valid any inferences are.

So for a survey of 1,000 respondents, the margin of error is around 3% at the 95% confidence level (this last figures indicates there is only a 5% probability that the findings were the result of chance). If a news story says Ed Miliband is leading David Cameron by 42% to 37% in the polls, we know this falls within the stated margin of error, since Ed Miliband’s true position may be 39% (42% – 3%) and David Cameron’s may be 40% (37% + 3%).

The difficulty from the pollster’s point of view is that creating a truly random sample is costly and time-consuming. So recently, non-probability sampling has enjoyed favour, particularly in the US and now increasingly in the UK.

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