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 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;
- Other errors of collection, nonresponse, processing, or imputation of values for missing or inconsistent data.[3]
See also
References
- ↑ Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9
- ↑ Fritz Scheuren (2005). "What is a Margin of Error?", Chapter 10, in "What is a Survey?", American Statistical Association, Washington, D.C. Accessed 2008-01-08.
- ↑ 3.0 3.1 U.S. Census Bureau. March 2012. Introduction. Quarterly Financial Report for Manufacturing, Mining, Trade, and Selected Service Industries. Fourth Quarter 2011. p. xxi