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]

  • Coverage errors, such as failure to accurately represent all population units in the sample, or the inability to obtain information about all sample cases;
  • Response errors by respondents due for example to definitional differences, misunderstandings, or deliberate misreporting;
  • Mistakes in recording the data or coding it to standard classifications;
  • Pseudo-opinions given by respondents when they have no opinion, but do not wish to say so
  • Other errors of collection, nonresponse, processing, or imputation of values for missing or inconsistent data.[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]

See also

References

  1. ↑ Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9
  2. ↑ Fritz Scheuren (2005). "What is a Margin of Error?", Chapter 10, in "What is a Survey? Archived 2013-03-12 at the Wayback Machine", American Statistical Association, Washington, D.C. Accessed 2008-01-08.
  3. 1 2 U.S. Census Bureau. March 2012. Introduction. Quarterly Financial Report for Manufacturing, Mining, Trade, and Selected Service Industries. Fourth Quarter 2011. p. xxi
  4. ↑ Kalton, Graham. Introduction to survey sampling. Vol. 35. Sage, 1983.
  5. ↑ Salant, Priscilla, and Don A. Dillman. "How to Conduct your own Survey: Leading professional give you proven techniques for getting reliable results." (1995).
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