What is a subset of data randomly selected from a population called?

A subset of data randomly selected from a population is known as a sample. In statistical analysis, a sample is important because it allows for inferences to be made about a larger population based on the characteristics observed in this smaller group. This method is often employed due to practical constraints, such as time, cost, or access to the entire population.

A sample is representative of the population from which it is drawn, meaning that the findings from the sample can help to predict or generalize outcomes for the broader population, provided that the sample is selected randomly and adequately reflects the population's diversity.

Understanding the concept of a sample is critical in cost management and analysis, where making decisions based on complete populations may not always be feasible. Proper sampling techniques can lead to valid conclusions while minimizing biases and errors.