What is sampling bias in data collection?

• A. When every group is equally represented.
• B. When data has no missing values.
• C. When data is collected from a single source only.
• D. When some groups or periods are over- or under-represented, skewing results.

Answer: (D)

Sampling bias happens when the data collected doesn’t reflect the population you care about. When some groups or time periods appear more often or less often in the sample than they do in the real world, the results get pulled in that direction and aren’t representative. This is exactly what over- or under-representation does to the findings, making them less generalizable. For example, surveying only people at a gym to judge overall activity levels would over-represent exercisers and under-represent others, biasing the outcome. So the key idea is that some groups or periods are unevenly represented, skewing the results.