Sampling bias occurs when a sample statistic does not accurately reflect the true value of the parameter in the target population, for example, when the average age for the sample observations does not accurately reflect the true average of the members of the target population. Typically, sampling bias focuses on one of two types of statistics: averages and ratios. The sources of sampling bias for these two types of statistics derive from different sources; consequently, these will be treated separately in this entry.
For survey researchers, sampling biases for averages derive from three sources: (1) imperfect sampling frames, (2) nonresponse bias, and (3) measurement error. Mathematical statisticians may also consider biases due to sources such as using the sample size (n) instead of ...
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