FAQ: Can you please clarify the definition of a sampling error as students often get confused between sampling error and non-sampling error? (3.10)

Suggested new description for the Senior Secondary Guide glossary:

Sampling Error

The error that arises as a result of taking a sample from a population rather than using the whole population.

An estimate of a population parameter, such as a sample mean or sample proportion, is likely to be different for different samples (of the same size) taken from the population and each estimate is likely to be different from the true population parameter. Sampling error is one of two reasons for the difference between an estimate and the true, but unknown, value of the population parameter. The other reason is non-sampling error. Even if a sampling process has no non-sampling errors (and therefore no bias) then estimates from different samples (of the same size) will vary from sample to sample.

The sampling error for a given sample is unknown but when the sampling is random, the maximum likely size of the sampling error is called the margin of error.

Click here to read the definitions of  sampling error, non-sampling and margin of error from the TKI website.

  • (Last updated: 13/07/17. Added: 24/10/12)