Non-sampling error
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 erro
er 10, in "What is a Survey? Archived 2013-03-12 at the Wayback Machine", American Statistical Association, Washington, D.C. Accessed 2008-01-08.</ref>
Non-sampling errors in survey estimates can arise from:[1]
- 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.[1]
An excellent discussion of issues pertaining to non-sampling error can be found in several sources such as Kalton (1983)[2] and Salant and Dillman (1995),[3]
See also
References
- ^ a b U.S. Census Bureau. March 2012. Introduction. Quarterly Financial Report for Manufacturing, Mining, Trade, and Selected Service Industries. Fourth Quarter 2011. p. xxi
- ^ Kalton, Graham. Introduction to survey sampling. Vol. 35. Sage, 1983.
- ^ Salant, Priscilla, and Don A. Dillman. "How to Conduct your own Survey: Leading professional give you proven techniques for getting reliable results." (1995).
 | This statistics-related article is a stub. You can help Wikipedia by expanding it. |