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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteTo evaluate an election poll, first check who it surveyed, how respondents were recruited, and when and how the questions were asked. Then read the margin of sampling error as a limited measure of uncertainty—not a guarantee of accuracy—and compare only polls that measure similar populations in similar ways. A topline number or a large sample alone cannot establish that a poll is reliable.
Start with who the poll represents
Find the poll’s target population: all adults, registered voters, likely voters, or another defined group. Also check the geography and the election being measured, such as a primary or a general election. These are different populations and questions. An adult poll is not automatically an estimate of how voters will vote, and a poll in one jurisdiction cannot stand in for another.
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Pollsters should disclose the population and methods behind their estimates. AAPOR’s Best Practices for Survey Research describes the importance of transparent reporting.
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Check when and how people were surveyed
Field dates and question wording
Look for the interview dates, then read the exact vote-choice question. Candidate names and order, undecided options, and preceding context can affect what respondents hear and how they answer. A poll records answers collected during a particular period; it does not describe opinion indefinitely. AAPOR’s Journalist’s Guide to Understanding Polls & Surveys discusses how to interpret poll methodology and results.
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Recruitment and mode
Check whether respondents were selected using a probability design or recruited through a nonprobability approach, and whether they answered online, by phone, or another mode. Mode alone does not tell you whether a poll is good or bad. What matters is how participants entered the survey and whether the disclosed design supports claims about the stated population.
Probability samples have a statistical basis for calculating a margin of sampling error. AAPOR cautions that applying a conventional sampling-error margin to a nonprobability sample can be misleading. The poll’s methods should explain the sample design and what its uncertainty claims mean.
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What a margin of error does—and does not—tell you
A margin of sampling error summarizes sampling variability under the assumptions of a probability design. It is not a guarantee that the true result falls inside the stated range, and it does not measure every source of error. It does not account for problems such as nonresponse bias, coverage gaps, question measurement, data processing, or an inaccurate likely-voter model. AAPOR explains these limits in its Polling Accuracy guidance.
For example, a reported candidate share with a margin of sampling error should not be treated as certainty about who is ahead. A close estimate may be consistent with either candidate leading, while other sources of error remain outside the margin. The margin also does not establish that the poll is accurate overall.
Subgroups need more caution
A result for a subgroup—such as voters of a particular age—is based on fewer respondents than the full sample. Its sampling error is therefore larger than the full-sample margin, so a small subgroup lead or apparent shift may be inconclusive. AAPOR’s Election Polling Resources covers the distinction between full-sample and subgroup uncertainty.
Understand weighting and nonresponse
Weighting changes how much each respondent counts so that measured characteristics align with population benchmarks. It can adjust observed imbalances, but it relies on the variables and assumptions used; it cannot prove that every relevant difference between respondents and nonrespondents has been removed.
A low response rate, by itself, does not reveal the size or direction of any bias. The concern is whether respondents and people who did not respond differ on characteristics relevant to the result, especially when the adjustment does not capture those differences. AAPOR treats nonresponse bias as distinct from sampling error.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Pew Research Center’s 2024 Election Methodology illustrates the detail a pollster may disclose. Its 2024 post-election American Trends Panel survey had 9,609 respondents and a reported full-sample margin of sampling error of ±1.5 percentage points. Pew describes weights that account for selection probabilities and nonresponse at multiple stages and calibration to population benchmarks; for that survey, the weights were also calibrated to turnout and presidential vote preference. Those figures describe that specific survey, not a standard every poll should meet.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Compare polls before calling something a trend
A poll is a snapshot, not a prediction. AAPOR states: “Like all polls, election polls represent a snapshot in time, and they are not meant to be predictive of an outcome.” An apparent change between two polls may reflect changing opinion, differences in design, or both.
When comparing polls, check these factors together:
- Population and geography: adults, registered voters, or likely voters—and the area covered.
- Field period: interview dates and timing relative to events.
- Sampling and recruitment: probability or nonprobability design and how respondents were reached.
- Question and mode: exact wording, answer options, question order, and online, phone, or other method.
- Weighting: benchmark variables, adjustments, and turnout assumptions.
- Uncertainty: whether the result is full-sample or subgroup, and what the stated margin covers.
- Disclosure: whether the pollster provides enough methodological detail to assess the result.
Comparisons within the same poll series can be especially useful when the population, question, and methods remain stable; note any changes in the series. A trend is more persuasive when comparable measurements show movement across time or across multiple polls, rather than when one poll differs from another with a different design. Poll averages can summarize several snapshots, but they cannot remove shared errors or turn polls into forecasts.
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A practical reading sequence
- Identify the target: note the population, geography, and election.
- Locate the field dates: establish when the responses were collected.
- Read the question: check wording, candidate order, answer choices, and context.
- Inspect the sample: find the recruitment method, survey mode, and whether the design is probability or nonprobability.
- Interpret uncertainty: determine what the margin covers, and avoid applying a full-sample margin to subgroups.
- Review weighting and disclosure: look for the benchmarks and adjustments, then assess what the pollster explains about its methods.
- Compare like with like: use polls with similar populations, timing, questions, and methods before inferring a trend.
There is no single figure that establishes whether a particular election poll is accurate. Historical performance varies by election, pollster, geography, and method; assess each poll from its own disclosure and compare it with measures of a similar population taken at a similar time.
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