In statistics, non-sampling error is a catch-all term for the deviations of estimates from their true values that are not a function of the sample chosen, including various systematic errors and random errors that are not due to sampling.
[1] Non-sampling errors are much harder to quantify than sampling errors.
[2] Non-sampling errors in survey estimates can arise from:[3] An excellent discussion of issues pertaining to non-sampling error can be found in several sources such as Kalton (1983)[4] and Salant and Dillman (1995),[5] This statistics-related article is a stub.
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