What is a consequence of sampling bias in a study?

• A. It increases the sample size and reduces error.
• B. It can skew results and misrepresent the population.
• C. It guarantees generalizability of findings.
• D. It eliminates measurement error.

Answer: (B)

Sampling bias happens when the way participants are chosen makes some groups more likely to be included than others, so the sample isn’t representative of the whole population. This systematic skew means the study’s results reflect the biased sample rather than the true population, producing biased estimates and a misrepresentation of what’s true for everyone. Because of that, the findings don’t generalize well beyond the study, lowering external validity. Merely increasing the number of participants doesn’t fix this; bias can persist even with a large sample. Measurement error, on the other hand, is about how data are collected, not about who is included in the sample.