Which statement best describes why selection bias occurs?

• A. It occurs when data are missing completely at random.
• B. It occurs when the sampling method is non-random, leading to unrepresentative results.
• C. It occurs due to measurement instruments inaccuracies.
• D. It occurs when the sample size is too large.

Answer: (B)

Selection bias shows up when the way you pick participants makes the sample systematically different from the population. If the sampling method is not random, some groups are more likely to be included than others, so the results reflect those groups more than others and don’t represent the whole population. That non-random selection is what causes the bias. By contrast, data missing completely at random wouldn’t bias results because the missingness isn’t related to the variables studied. Measurement instrument inaccuracies create errors in the outcomes measured, not in who was chosen to be in the study. A very large sample size doesn’t cause bias; it generally improves precision and reduces random error.