What is error sampling? Explain sampling and Non-sampling error.
Answers
Non-sampling error is caused by factors other than those related to sample selection. It refers to the presence of any factor, whether systemic or random, that results in the data values not accurately reflecting the 'true' value for the population.
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Answer:
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.)
What is error sampling?
Sampling error is a statistical error that occurs when an analyst does not select a sample that represents the entire population of data. The results found in the sample thus do not represent the results that would be obtained from the entire population. In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population.