What is sampling bias?

• A. A systematic error due to nonrepresentative samples.
• B. A systematic error due to leading questions.
• C. The margin of error around the estimate.
• D. Random sampling error.

Answer: (A)

Sampling bias happens when the group chosen for a study doesn’t reflect the larger population, so the results are systematically off. It’s a systematic error because the flaw is built into how the sample was selected, not just due to random chance. When certain groups are overrepresented or underrepresented in the sample, the estimated values (like percentages or support levels) don’t mirror the true population values.

For example, polling only people with landlines to gauge national opinion can overrepresent older or more suburban respondents and underrepresent younger or mobile-only individuals, leading to biased conclusions about the whole population.

Leading questions cause a different kind of bias, known as measurement or question wording bias, by influencing how people respond rather than by who was included in the sample. The margin of error reflects the uncertainty around an estimate due to sampling variability, not a systematic bias. Random sampling error is the natural variation that occurs by chance, also not a bias.