Which statement best describes the purpose of random sampling in reducing bias?

• A. It helps ensure each member of the population has an equal chance of selection, reducing bias.
• B. It guarantees the sample will reflect the population perfectly.
• C. It increases bias by over-representing some groups.
• D. It makes data analysis more complex but unnecessary.

Answer: (A)

The main idea here is that random sampling gives every member of the population an equal chance of being chosen. This removes the researcher’s personal choices or unconscious preferences from who is included, so no particular group is more likely to be picked than another. By giving all members an equal shot, the sample becomes more representative of the whole population and bias from selection is reduced.

It’s important to note that random sampling doesn’t guarantee a perfect match to the population—there will still be some differences due to chance, especially with smaller samples. But because each member had an equal chance of selection, the process minimizes systematic bias that comes from nonrandom selection.

The other statements don’t fit because over-representing some groups would actually increase bias, randomness isn’t about making data analysis more complex or unnecessary, and the aim isn’t to guarantee perfect reflection but to reduce bias through equal opportunity of selection.