Short answer: The spread we’re seeing is definitely outside the bounds of what you’d expect based on sampling error alone. To arrive at this conclusion, I took all the national polls since the beginning of October1 and ran 10,000 simulations estimating how wide the spread of the polls “should” be for Biden and Warren based on the sample size of each poll.2 For each simulation, I calculated the standard deviation (a measure of the spread of the polls), resulting in a distribution of what we’d expect to see as a result of sampling error alone. We would expect the actual standard deviation of the polls to fall within these intervals 95 or 99 percent of the time. And as you can see in the chart below, the spread between all the October polls is way outside the range of standard deviations for what we would expect — for both Biden and Warren.

For example, with Biden, we’d expect the standard deviation for polls to be about 2 percentage points, but it’s actually 3.5 points. It’s a similar situation for Warren — we’d expect the standard deviation to be between 2 and 3 points, but in fact it’s almost 5 points.

That suggests that it isn’t just sampling error that’s driving the differences we’re seeing — it implies there are some real methodological differences between the polls.