sampling error


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sampling error

[′samp·liŋ ‚er·ər]
(statistics)
That portion of the difference between the value of a statistic derived from observations and the value that it is supposed to estimate; attributed to the fact that samples represent only a portion of a population.

sampling error

the difference between the ‘true’ value of a characteristic within a population and the value estimated from a sample of that population. ‘Error’ occurs because no SAMPLE can be expected to exactly represent the parent population from which it was drawn. To minimize, and to be able to estimate, sampling error, it is necessary to ensure that the selection of the sample is RANDOM, and this is normally done by random numbers or systematic sampling. Sampling error is not the same as BIAS or systematic error, which may occur due to the process of data collection, but is nothing to do with the sample selection.
References in periodicals archive ?
All reported margins of sampling error include computed design effects for weighting.
The margin of sampling error is plus or minus four percentage points for the full sample as well as the sample of 855 registered voters.
The link discharge sampling error was less than 10 percent for all run sets, showing minimal variability across all runs, and tended to stabilize around 2 percent after more runs.
In a well-designed statistical sample, the sampling error is as small as we need it to be.
The sampling error probability refers to a statistical property of data underlying evidence offered to prove a relevant fact, such as the connection between the defendant's act and the plaintiff's harm.
Four tests were selected to evaluate effects of sampling error on the feasibility of detecting density dependence in natural populations.
Also, the values for sampling error variance are reported, along with the lower boundary of credibility values, and the unexplained variance.
If probability samples are used, estimates of sampling error can be made from the sample.
However, sampling errors also could have occurred when a portion was taken for analysis or when the samples were collected at the foundry.
This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes.