A selection method that ensures unbiased representation from a larger population is known as what?

The concept being described is representative sampling, which is designed to accurately reflect the characteristics of a larger population in a smaller sample. This method ensures that various subgroups within the population are proportionately represented, allowing the findings from the sample to be generalized to the broader population.

For instance, if you were studying a population that consists of various age groups, ethnicities, and socioeconomic statuses, representative sampling would ensure that each of these groups is included in the sample in the same proportion as they exist in the entire population. This method mitigates sampling bias and allows researchers to draw valid conclusions from their data.

In contrast, other methods like cluster sampling may involve dividing the population into clusters and randomly sampling some of these clusters, which can lead to bias if those clusters do not represent the overall population. Random sampling, while useful, may not guarantee that all subgroups are represented equally. Convenience sampling involves selecting individuals based solely on their availability, which often leads to significant bias and does not reflect the larger population accurately. Thus, representative sampling is the method that best aligns with the goal of ensuring unbiased representation.