A flawed sampling process that produces an unrepresentative sample.

• A. Sampling bias
• B. Random sampling
• C. Cross-sectional design
• D. Simple random sample

Answer: (A)

Sampling bias is a flawed sampling process that produces an unrepresentative sample. It happens when some members of the population are more likely to be included than others, so the sample doesn’t reflect the whole group. This can come from how participants are recruited, who responds, or systematic exclusions that skew the makeup of the sample. Because the sample doesn’t match the population, findings may not generalize beyond the studied group.

The other terms describe sound or distinct aspects of research design. Random sampling is a method that gives everyone an equal chance of being included, which reduces bias. A cross-sectional design refers to collecting data at a single point in time, not to how participants are sampled. A simple random sample is a specific way of selecting participants with equal probability, also aimed at reducing bias rather than introducing it.