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Sampling error

Definition

Sampling error refers to the difference between the results obtained from a sample survey and the actual results that would be obtained if the entire population were surveyed. It is caused by randomness and variability in selecting a sample.

Analogy

Imagine you have a bag of M&M's, and you want to know how many blue ones are in there. You randomly pick out 10 M&M's, count 6 blue ones. Now imagine if you had picked out 100 M&M's instead, you might get a different number of blue ones. The difference between what you got (6) and what the actual number is called sampling error.

Related terms

Sample size: The number of individuals selected for analysis in a sample. A larger sample size usually leads to lower sampling error.

Sample selection method: The process used to choose which individuals will be included in the survey or study. Different methods can result in different levels of sampling error.

Population characteristics: The attributes or qualities of the population being studied. Population characteristics can influence sampling error as they may affect how representative the sample is of the entire population.