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How to use sampling error in a sentence

Looking for sentences with "sampling error"? Here are some examples.

Sentence Examples
In addition to these caveats, sampling error due to analysis of an inadequate sample volume can also lead to a false-negative test result.
Because of concern for sampling error, documentation of regression requires an ample biopsy followed by examination of the entire liver.
This sampling error causes random fluctuations in allele frequencies called genetic drift.
This is because the statistical sampling error of the phase is inversely related to the squared coherence.
This will remind test users that the reliability coefficient in hand is not the population parameter and that the reliability estimate is affected by sampling error.
For example, the difference between a population mean and a sample mean is sampling error.
Usually, however, the systematic component of sampling error is very small in relation to its random component.
Statistical theory can provide estimates of sampling error for various sample sizesthat is, the precision of the estimates.
These estimates are not published because they may present too great a sampling error.
However, the survey results remain subject to errors, of which sampling error is only one component of the total survey error.
Given the large sample size, the majority of the estimates presented in this report have a small sampling error.
In our study, the data from smaller communities has a higher possibility of sampling error.
The margin of sampling error will be greater for regional and provincial sub-samples, as presented below.
To make it less likely that the measured net effect of a program is the result of sampling error, one should use as large a sample as possible.
Of two estimates, the larger one will likely have a smaller percent sampling error.
Sampling techniques vary considerably in the expertise required to design the sample and to estimate sampling error.
The discrepancy between sampled values and population values is known as sampling error.
The main aim of stratification is to minimize sampling error for a given sample size.
There are two components to the sampling error, the sampling bias and the sampling variance.
For smaller subgroups the potential sampling error is larger.
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