Bias in Survey Sampling In survey sampling, bias refers to the tendency of a sample statistic to systematically over- or under-estimate a population parameter . Bias Due to Unrepresentative Samples A good sample is representative . This means that each sample point represents the attributes of a known number of population elements. Bias often occurs when the survey sample does not accurately represent the population. The bias that results from an unrepresentative sample is called selection bias . Some common examples of selection bias are described below. Undercoverage . Undercoverage occurs when some members of the population are inadequately represented in the sample. A classic example of undercoverage is the Literary Digest voter survey, which predicted that Alfred Landon would beat Franklin Roosevelt in the 1936 presidential election. The survey sample suffered from undercoverage of low-income voters, who tended to be Democrats.