A sample that fairly represents a population because each member has an equal chance of inclusion.

A sample that fairly represents a population because each member has an equal chance of inclusion.

• A. Random sampling
• B. Simple random sample
• C. Sampling frame
• D. Representative sample

Answer: (A)

The key idea is that the sample is chosen by chance so every member of the population has an equal shot at being included. This equal-probability approach is what makes random sampling effective at producing a group that reflects the population without systematic bias. Simple random sampling is a concrete way to implement this principle, ensuring each individual has the same chance of selection, typically through a random process. A sampling frame is simply the list from which you draw elements, not a statement about how participants are chosen; a representative sample describes how well the sample matches the population, which is the outcome you aim for, not the selection mechanism. So this description best captures the concept of random sampling.

The key idea is that the sample is chosen by chance so every member of the population has an equal shot at being included. This equal-probability approach is what makes random sampling effective at producing a group that reflects the population without systematic bias. Simple random sampling is a concrete way to implement this principle, ensuring each individual has the same chance of selection, typically through a random process. A sampling frame is simply the list from which you draw elements, not a statement about how participants are chosen; a representative sample describes how well the sample matches the population, which is the outcome you aim for, not the selection mechanism. So this description best captures the concept of random sampling.