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A population is the entire group that you want to draw conclusions about. A sample is the specific group that you will collect data from. The size of the sample is always less than the total size of the population. In research, a population doesn’t always refer to people.
A subgroup of the members of population chosen for participation in the study is called sample. The population consists of each and every element of the entire group. On the other hand, only a handful of items of the population is included in a sample.
Population vs sample is a crucial distinction in statistics. Typically, researchers use samples to learn about populations. Let’s explore the differences between these concepts! Population: The whole group of people, items, or element of interest. Sample: A subset of the population that researchers select and include in their study.
This tutorial provides a quick explanation of the difference between a sample and a population, including several examples.
Population vs Sample — Differences and examples. While the population provides a comprehensive overview of the entire group under study, the sample, on the other hand, allows researchers to draw inferences and make generalizations about the population.