Margin of error
CLEP American Government, Chapter 37
Margin of error
Even a well-selected probability sample will not reproduce the population perfectly. Sampling error is the chance difference that arises because researchers observe some members rather than everyone. If the same design drew many samples, the estimates would vary around the population value. Larger effective samples usually reduce that variation. Under a simple random design, quadrupling the sample size roughly halves the standard error; the size of a large population matters much less.
A margin of error is the half-width added to and subtracted from an estimate to form a confidence interval at a stated level. An estimate of 44 percent with a margin of plus or minus four percentage points is commonly displayed as an interval from 40 to 48 percent. The confidence level describes the long-run success of intervals produced by the method, not certainty about each respondent or a promise that this one estimate is correct.
Sampling error is only one part of total survey error. A margin does not measure omitted groups, self-selection, systematic nonresponse, leading language, inaccurate answers, interviewer pressure, processing mistakes, or opinion change after the interviews. If a biased frame excludes a distinctive group, increasing the number selected from that same frame can narrow the interval around a systematically mistaken estimate.
Subgroups also contain fewer cases than the full sample. A margin reported for 1,500 adults should not be attached unchanged to an estimate based on 180 adults in one age group.
Read every margin conditionally: it describes random variation if the sampling assumptions hold. Then inspect the rest of the chain.
Video lesson: Science Behind the News: Opinion Polls & Random Sampling
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