Survey margin of error and sample size matter: here’s why

In almost any discussion of polling about the very close presidential race between Vice President Kamala Harris and former President Donald Trump, you will hear the phrase “within the survey error” These words signal that it is tight race with no clear leadereven if one of them has a slightly higher percentage of support, approximately 48% to 47%.

Local opinion poll conducted by Oregonian/OregonLive in October 2024.

How Quinnipiac University Poll Directorwho has been following the public pulse on politics and elections for the past 30 years, I’ve noticed that people have been paying more attention to this technical term since at least 2016.

For example, that year some polls in Florida showed that Hillary Clinton was ahead by only a couple of percentage points. Trump. Journalists and the public largely—and incorrectly—understood that the apparent popular vote led to villainy. Clinton is likely to win.

But that 1 or 2 percentage points was within the margin of error of their polls. And Clinton lost Florida. In a poll about a political race, the margin of error tells readers the likely range of election results.

What is error?

A survey is one or more questions that are asked to a small group of people and used to gauge the opinions of a larger group of people. The margin of error is a mathematical calculation of how accurate a poll’s results are—how closely the answers given by a small group match the views of the larger group.

If all members of a large group were interviewed, there would be no margin of error. But reaching so many people is difficult, difficult and expensive. The US Census Bureau spent $13.7 billion over several years in its latest attempt to count every person in the United States every 10 years, and it’s still failed to include everyone.

Social scientists don’t have the time or money, so they use smaller samples of the population. They seek to identify representative samples in which all members of a larger group have a chance of being included in the survey.

Group size is important

The calculation of how close a poll is to the views of the majority of the population is based on the size of the group polled.

For example, a sample of 600 voters will have a larger margin of error—about 4 percentage points—than a sample of 1,000 voters, which has a margin of error of just over 3 percentage points.

The method of selecting the sample also matters: in 1936, Literary Digest magazine surveyed people in the presidential election by sending surveys to phone owners, car owners and country club members. Everyone in this group was relatively affluent, so they were not representative of the entire voting population in the United States. Calculating the margin of error would be meaningless because the sample did not cover all segments of the population.

Specific example

Let’s use an example of how to understand the margin of error. If a poll shows that 47% of the polled group supports Candidate A, and the margin of error is plus or minus 3 percentage points, that means the percentage of the population supporting Candidate A is likely to be between 44% (47 minus 3 percentage points). ) and 50% (47 plus 3).

One quick note: Most polls report a margin of error along with another technical term: “confidence interval” In the most accurate polling reports, you may see a sentence at the end that says something like, “The margin of error is plus or minus 3 percentage points at the 95% confidence interval.” What this all means is this: imagine that 100 different random samples of the same size were selected from a larger group, and then the same questions were asked in a survey. A 95% confidence interval means that 95% of the time, other survey responses will be within 3 percentage points of the responses in this survey.

Comparison of support between candidates

The concept of margin of error becomes more complex when considering the difference in support between the two candidates. If the margin of error is plus or minus 3 percentage points, the margin of error for the difference between the two is roughly double that – or 6 percentage points in this example.

This is because the margin of error here is combined and relates not only to the percentage of votes for Candidate A, but also to the percentage of votes for the other candidate.

Looking back at 2016 again, finale Quinnipiac University poll in Florida ahead of Election Day showed Clinton with 46% support and Trump with 45% support. The margin of error was 3.9 percentage points, meaning Clinton would likely receive between 42.1% and 49.9% of the vote, while Trump would likely receive between 41.1% and 48.9% of the vote.

The actual result was that Trump won Florida with 48.6% of the vote.compared to Clinton’s 47.4%. These results were within our poll’s margin of error, meaning we were right to say it was “too close to forecast” and we would be wrong to say Clinton was in the lead.

Elections in 2024 will be closed

In the current election cycle, many media reports about the polls not including information about the error.

Withholding this information or downplaying its significance can help the media provide a quick and simple picture of the state of the race. Technology may seem precise in the modern age of the Internet and artificial intelligence.

But polls are not that accurate. This is an inexact science. The job of a sociologist is to take snapshots of the complexities of human nature at a particular point in time. People’s minds may change and new information may emerge as campaigns develop.

As the presidential election comes to a close, our polls show that Quite a tight and steady racehowever, the majority of voters tell us that their opinion is accepted. With the margin of error between presidential candidates well within the margin of error in swing states, polls for the fall 2024 election are telling Americans to hold their breath and make sure they vote because it’s likely to be a squeaker.