Which of the following best describes quota sampling?

Quota sampling is best described as a non-probability technique that involves dividing the population into subgroups, or strata, and then selecting a specific number of participants from each subgroup to ensure representation. This method allows researchers to control for certain characteristics in the sample, ensuring that it reflects the diversity of the population regarding those characteristics. By setting quotas for different groups, researchers can obtain a sample that meets their specific criteria, which is particularly useful in studies aiming to analyze attitudes or opinions among distinct demographic segments.

This technique differs from random sampling, where every member of the population has an equal chance of being selected, hence the first option does not accurately describe quota sampling. The idea of using the entire population for the sample, as mentioned in the third choice, aligns more with census methods, which are not the same as quota sampling. Lastly, while statistical significance is a consideration in many research methods, quota sampling does not inherently require a focus on achieving statistical significance; it is primarily about ensuring diverse representation within the sample.