Sampling Error

DEFINITION of 'Sampling Error'

A statistical error to which an analyst exposes a model simply because he or she is working with sample data rather than population or census data. Using sample data presents the risk that results found in an analysis do not represent the results that would be obtained from using data involving the entire population from which the sample was derived.

BREAKING DOWN 'Sampling Error'

The use of a sample relative to an entire population is often necessary for practical and/or monetary reasons. Although there are likely to be some differences between sample analysis results and population analysis results, the degree to which these can differ is not expected to be substantial.

Methods of reducing sampling error include increasing the sample size and ensuring that the sample adequately represents the entire population.

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RELATED FAQS
  1. How do researchers ensure that a simple random sample is an accurate representation ...

    Researchers employ several safeguards to ensure that a simple random sample accurately represents a larger population. They ... Read Full Answer >>
  2. How can a representative sample lead to sampling bias?

    A representative sample, like any other type of sample, by its very nature leads to a degree of sampling bias, or sampling ... Read Full Answer >>
  3. What percentage of the population do you need in a representative sample?

    Technically, a representative sample requires only whatever percentage of the statistical population is necessary to replicate ... Read Full Answer >>
  4. What are the advantages of using a simple random sample to study a larger population?

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