Which option best defines sampling bias?

• A. A bias due to measurement error
• B. A problem that occurs when a sample is not representative of the population from which it is drawn
• C. A bias introduced by random sampling
• D. A bias due to large sample size

Answer: (B)

Sampling bias arises when the group chosen for a study does not accurately reflect the population being studied, so the results aren’t truly representative. This happens if you rely on a convenient subset, such as volunteers or easily accessible individuals, which can over- or under-represent certain characteristics and skew conclusions. That’s why this option best defines sampling bias. By contrast, measurement error comes from inaccuracies in data collection or instruments, not from who is included. Random sampling aims to reduce bias, so it isn’t a source of bias itself. And a larger sample size generally lowers sampling error and improves representativeness rather than introducing bias.