What is random sampling?

What is random sampling?

• A. A sample taken in a way that all potential observations of the population have an equal chance of being chosen.
• B. A sample chosen by the researcher’s convenience.
• C. A sample with repeated measurements.
• D. A sample that excludes outliers.

Answer: (A)

Random sampling gives every member of the population an equal chance of being selected. This equal-probability approach minimizes selection bias, so the sample is more likely to reflect the population’s characteristics. Because each element has the same opportunity to be chosen, we can use probability theory to quantify sampling error and build confidence in inferences about the population. This is different from convenience sampling, where you pick readily available individuals, which can skew results; it also avoids relying on repeated measurements of the same unit or deliberately excluding outliers, both of which can bias estimates. Even with random sampling, there is still some variation from sample to sample, but larger samples reduce this random error and improve representativeness.

Random sampling gives every member of the population an equal chance of being selected. This equal-probability approach minimizes selection bias, so the sample is more likely to reflect the population’s characteristics. Because each element has the same opportunity to be chosen, we can use probability theory to quantify sampling error and build confidence in inferences about the population. This is different from convenience sampling, where you pick readily available individuals, which can skew results; it also avoids relying on repeated measurements of the same unit or deliberately excluding outliers, both of which can bias estimates. Even with random sampling, there is still some variation from sample to sample, but larger samples reduce this random error and improve representativeness.