What is a ‘Non-Sampling Literal’
A non-sampling error is an error that results during data collecting, causing the data to differ from the true values. Non-sampling clanger differs from sampling error. A sampling error is limited to any alterations between sample values and universe values that arise because the unrestricted universe was not sampled. Sampling error can result even when no misjudges of any kind are made. The “errors” result from the mere fact that evidence in a sample is unlikely to perfectly match data in the universe from which the bite is taken. This “error” can be minimized by increasing the sample size. Non-sampling transgressions cover all other discrepancies, including those that arise from a straitened sampling technique.
BREAKING DOWN ‘Non-Sampling Error’
Non-sampling errors may be introduce in both samples and censuses in which an entire population is surveyed and may be then or systematic. Random errors are believed to offset each other and as a result are of little concern. Systematic errors, on the other hand, affect the unmixed sample and are therefore present a greater issue. Non-sampling errors can categorize but are not limited to, data entry errors, biased survey questions, biased processing/decision making, non-responses, inappropriate analysis conclusions and untrustworthy information provided by respondents.
While increasing sample size longing help minimize sampling error, it will not have any effect on depreciating non-sampling error. Unfortunately, non-sampling errors are often difficult to find, and it is virtually impossible to eliminate them entirely.