Assessment and Learning in Knowledge Spaces (ALEKS) Practice Exam

What is the difference between a sample and a population in statistics?

1. A sample includes all members of a specified group

2. A population is a subset of members used for analysis

3. A sample is a subset of a population used for analysis

4. A population refers to data from single observations only

The correct answer is: A sample is a subset of a population used for analysis

In statistics, the concept of a sample and a population is fundamental to understanding how data is collected and analyzed. A sample is indeed a subset of a population that is selected for analysis. This allows researchers to make inferences about the entire population without needing to collect data from every single member, which can be impractical or impossible in many cases. Using a sample is essential as it provides a manageable way to gather insights while minimizing resources and time. The sample should ideally be representative of the population to ensure that the findings can be generalized back to the population. The process of selecting a sample can influence the results significantly; therefore, methods such as random sampling are often employed to enhance the validity of the results obtained from the sample. In contrast, a population encompasses all members of a specified group and includes every single data point of interest. Thus, the distinction lies in the size: the population is the larger group, while the sample is just a portion of that group meant to represent it for analytical purposes.