Which statement best distinguishes random sampling from convenience sampling and its implications for generalizability?

Which statement best distinguishes random sampling from convenience sampling and its implications for generalizability?

• A. It gives every population member an equal chance to participate.
• B. Random sampling supports generalizability, while convenience sampling may bias results.
• C. It guarantees that the sample will mirror the population exactly.
• D. It eliminates all sampling bias.

Answer: (B)

The main idea here is how sampling methods affect generalizability. Random sampling aims to give every member of the population an equal chance to be included, which helps create a sample that, on average, resembles the population. This representativeness supports generalizing findings beyond the sample because biases that come from who ends up in the study are minimized. Convenience sampling, by contrast, relies on participants who are easy to reach, which often means the sample isn’t representative and findings may reflect characteristics of that accessible group rather than the broader population. That potential bias limits how confidently we can generalize. The other statements are off because random sampling doesn’t guarantee an exact mirror of the population, and no sampling method eliminates all bias.

The main idea here is how sampling methods affect generalizability. Random sampling aims to give every member of the population an equal chance to be included, which helps create a sample that, on average, resembles the population. This representativeness supports generalizing findings beyond the sample because biases that come from who ends up in the study are minimized. Convenience sampling, by contrast, relies on participants who are easy to reach, which often means the sample isn’t representative and findings may reflect characteristics of that accessible group rather than the broader population. That potential bias limits how confidently we can generalize. The other statements are off because random sampling doesn’t guarantee an exact mirror of the population, and no sampling method eliminates all bias.