Which statement best describes the difference between a population and a sample?

The distinction between a population and a sample is a fundamental concept in statistics. A population refers to the entire set of individuals or items that share a common characteristic and are of interest in a particular study. This could be all voters in a country, all students at a university, or all possible measurements for a certain phenomenon. Conversely, a sample is a smaller group selected from this population, which is used to make inferences or draw conclusions about the entire population.

Choosing the statement that asserts that a population includes all members of a defined group while a sample is just a subset of that population accurately captures this relationship. It highlights that the sample is meant to represent the population and allows researchers to make estimations and generalizations based on observations from the sample without needing to study every single member of the population.

The other statements misrepresent the relationship. For instance, one mistakenly claims that a population is a subset of a sample, which is incorrect as it implies that a smaller group (the sample) encompasses the whole (the population). Another option incorrectly suggests that a sample includes all members of a defined group, which would negate the very definition of a sample as being smaller than the population. Lastly, stating that there is no difference fails to recognize the critical