Most people intuitively understand the idea of sampling. One taste from a drink tells us whether it is sweet or sour. If we select a few employment records out of a complete set, we usually assume our selection reflects the characteristics of the full set. If some of our staff favors a flexible work schedule, we infer that others will also. These examples vary in their representativeness, but each is a sample.
The basic idea of sampling is that by selecting some of the elements in a population, we may draw conclusions about the entire population. A population element is the subject on which the measurement is being taken. It is the unit of study. For example, each office worker questioned about a flexible work schedule is a population element, and each business account analysed is an element of an account population. A population is the total collection of elements about which we wish to make some inferences. All office workers in the firm compose a population of interest; all 4,000 files define a population of interest. A census is a count of all the elements in a population. If 4,000 files define the population, a census would obtain information from every one of them.
