Definition of Non-sampling error:
A non-sampling error is a statistical term that refers to an error that results during data collection, causing the data to differ from the true values. A non-sampling error differs from a sampling error. A sampling error is limited to any differences between sample values and universe values that arise because the sample size was limited. (The entire universe cannot be sampled in a survey or a census.).
That arises from inaccurate sampling frame, data clarification or verification methods, reporting or coding of data, and/or specifications. It may also arise from poorly designed survey questionnaires, improper sample allocation and selection procedures, and/or errors in estimation methodology.
A sampling error can result even when no mistakes of any kind are made. The "errors" result from the mere fact that data in a sample is unlikely to perfectly match data in the universe from which the sample is taken. This "error" can be minimized by increasing the sample size.
How to use Non-sampling error in a sentence?
- Systematic non-sampling errors are worse than random non-sampling errors because systematic errors may result in the study, survey or census having to be scrapped.
- A non-sampling error refers to either random or systematic errors, and these errors can be challenging to spot in a survey, sample, or census. .
- A non-sampling error is a term used in statistics that refers to an error that occurs during data collection, causing the data to differ from the true values. .
- The higher the number of errors, the less reliable the information.
- When non-sampling errors occur, the rate of bias in a study or survey goes up. .
Meaning of Non-sampling error & Non-sampling error Definition