B. Samples and Sampling

Why Sample?

Sampling is done in a wide variety of research settings. Listed below are a few of the benefits of sampling:

  1. Reduced cost: It is obviously less costly to obtain data for a selected subset of a population, rather than the entire population. Furthermore, data collected through a carefully selected sample are highly accurate measures of the larger population. Public opinion researchers can usually draw accurate inferences for the entire population of the United States from interviews of only 1,000 people.
  2. Speed: Observations are easier to collect and summarize with a sample than with a complete count. This consideration may be vital if the speed of the analysis is important, such as through exit polls in elections.
  3. Greater scope: Sometimes highly trained personnel or specialized equipment limited in availability must be used to obtain the data. A complete census (enumeration) is not practical or possible. Thus, surveys that rely on sampling have greater flexibility regarding the type of information that can be obtained.

It is important to keep in mind that the primary point of sampling is to create a small group from a population that is as similar to the larger population as possible. In essence, we want to have a little group that is like the big group. With that in mind, one of the features we look for in a sample is the degree of representativeness - how well does the sample represent the larger population from which it was drawn? How closely do the features of the sample resemble those of the larger population?

There are, of course, good and bad samples, and different sampling methods have different strengths and weaknesses. Before turning to specific methods, a few specialized terms used in sampling should be defined.

Sampling Terminology

Samples are always drawn from a population, but we have not defined the term "population." By "population" we denote the aggregate from which the sample is drawn. The population to be sampled (the sampled population) should coincide with the population about which information is wanted (the target population). Sometimes, for reasons of practicality or convenience, the sampled population is more restricted than the target population. In such cases, precautions must be taken to secure that the conclusions only refer to the sampled population.

Before selecting the sample, the population must be divided into parts that are called sampling units or units. These units must cover the whole of the population and they must not overlap, in the sense that every element in the population belongs to one and only one unit. Sometimes the choice of the unit is obvious, as in the case of the population of Americans so often used for opinion polling. In sampling individuals in a town, the unit might be an individual person, the members of a family, or all persons living in the same city block. In sampling an agricultural crop, the unit might be a field, a farm, or an area of land whose shape and dimensions are at our disposal. The construction of this list of sampling units, called a frame, is often one of the major practical problems.

The Gallup Poll A Familiar Example of Sampling

Most of us are familiar with sampling at some level through seeing reports about levels of popular opinion about some current topic. Newspapers and television programs are filled with references to the current state of popular opinion.

One of the most prestigious firms in the polling business is The Gallup Organization. Their web site has an excellent description of why sampling is common in social science research, how it is conducted, and some other issues. For example, the page contains the following statement about the value of sampling:

The basic principle: a randomly selected, small percent of a population of people can represent the attitudes, opinions, or projected behavior of all of the people, if the sample is selected correctly.

The page can be found here.