What is the primary difference between population and sample in research?

The primary difference between population and sample in research is that the population refers to the entire group that is the subject of study, while a sample is a smaller subset selected from that larger group. Understanding this distinction is crucial for researchers because it affects how they can generalize their findings.

Populations can include all individuals or observations that meet certain criteria relevant to a research question, such as all adults in a city, all students at a university, or all plants of a particular species. However, it is often impractical or impossible to gather data from an entire population due to constraints like time, cost, or accessibility.

On the other hand, a sample is a manageable number of individuals selected from the population, which is intended to represent the larger group. Researchers use statistical techniques to ensure that the sample reflects the characteristics of the population, enabling them to make inferences about the population based on the data collected from the sample. This distinction is foundational in statistical analysis and influences the validity of the conclusions drawn from research findings.