Sampling

Sample Design

Probability samples should be distinguished from “samples of convenience”(also called“grabsamples”). A typical sample of convenience comprises the investigator's students in an introductory course. A “mall sample”consists of the people willing to be interviewed on certain days at certain shopping centers. This too is a convenience sample. The reason for the nomenclature is apparent, and so is the downside: the sample may not represent any definable population larger than itself.

To draw a probability sample, we begin by identifying the population of interest. The next step is to create the “sampling frame,” a list of units to be sampled. One easy design is simple random sampling. For instance, to draw a simple random sample of 100 units, choose one unit at random from the frame; put this unit into the sample; choose another unit at random from the remaining ones in the frame; and so forth. Keep going until 100 units have been chosen. At each step along the way, all units in the pool have the same chance of being chosen.

Simple random sampling is often practical for a population of business records, even when that population is large. When it comes to people, especially when face-to-face interviews are to be conducted, simple random sampling is seldom feasible: where would we get the frame? More complex designs are therefore needed. If, for instance, we wanted to sample people in a city, we could list all the blocks in the city to create the frame, draw a simple random sample of blocks, and interview all people in housing units in the selected blocks. This is a “cluster sample,” the cluster being the block.

Notice that the population has to be defined rather carefully: it consists of the people living in housing units in the city, at the time the sample is taken. There are many variations. For example, one person in each household can be interviewed to get information on the whole household. Or, a person can be chosen at random within the household. The age of the respondent can be restricted; and so forth. If telephone interviews are to be conducted, random digit dialing often provides a reasonable approximation to simple random sampling—for the population with telephones.

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