What distinguishes a population from a sample in research?

The correct answer is that a population includes the entire group of interest. In research, a population refers to the complete set of individuals or instances that meet a particular criterion for a study. This could be all the people living in a country, all the students in a school, or all the employees of a company, depending on what the researcher is studying.

Conversely, a sample is typically a subset of the population that is selected for the purpose of the study. Researchers use samples to make inferences about the characteristics of the larger population because studying the entire population may be impractical or impossible.

The distinction is crucial for understanding how research findings can be generalized. When researchers draw conclusions based on a sample, they aim to ensure that it is representative of the larger population to validate their results.

The other options present misleading or incorrect interpretations of the concepts. For instance, stating that a population is larger than a sample doesn't capture the core definition of what a population is. Moreover, the claim that a sample is always biased does not reflect the reality that samples can be randomly selected and thus unbiased. Lastly, the assertion that a sample consists of different populations is inaccurate because a sample is derived from one specific population, not multiple.