Probability sampling

Sampling terms

Shortly, we will describe the four main methods of selecting probability samples. To understand and apply these methods, you first need to understand certain concepts and terms used in sampling.

Population. Your research question defines the group or population you want to learn about. Many small populations can be defined precisely. All students who graduated last year from your university would form a concrete, easily defined population. So would all staff of a certain business or all heads of households in a village. Many populations we choose to study, however, are harder to define with any accuracy. The population of a city, for example, exists only as an abstract concept. We may have an estimate of the population size, but at any moment the population changes: Some persons and families leave, others arrive. The same is true for many organizations and other groups we want to study. Because of constant changes in populations, researchers have to define a population as clearly as possible in concrete terms before preparing to select a sample. This is generally done by placing specific geographic, time, membership, or other limits on the abstract population. The specifically defined population is referred to as the target population. The target population is the population we want our sample to represent. Box 8.1 illustrates some target populations.

Box 8.1. Illustrative target populations All persons who have lived throughout the past six months in households in the city of Omdurman, Sudan, and were present during the month of March, 2005. All government ministries in Egypt with 500 or more full time staff, as reported on June 1, 2005. All patients admitted to the private hospitals   with at least 25 beds in Nairobi, Kenya, during the month of February, 2005. All editorials published on the editorial pages of the Times of London from September 12 through December 31, 2001. All households headed by women who lived full time in the Dar Elsalam camp for internally displaced persons during the week of May 23, 2005.

Notice that each definition creates a concrete, measurable population. The population for Omdurman, for example, is limited to persons who have lived in a household for the past six months and were present during the month of March, 2005. This rules out persons who live in hotels or who are temporary guests of persons living in Omdurman. The Egyptian example includes only full time staff of ministries with at least 500 employees and who were employed as of June 1, 2005. Each of the other populations has specific limits.

Sampling element. A sampling element or sampling unit is a single member or unit of the target population. This is the unit about which information will be obtained. Frequently, the sampling element is an individual, but as illustrated in Box 8.1, sampling elements may be organizations, editorials, or groups, such as households.

Sample frame. This is the list of all sampling elements from which the sample is selected.The sample frame is the practical, operational definition of the target population. Ideally, we begin by defining the target population for a given study and then search for a sampling frame that matches the target population as we have defined it.In practice, however, the process is often reversed. We sometimes begin with a general definition of the population and using this as a guide, search for and evaluate sampling frames until we find one that comes close to or is as close as possible to the definition of the target population and then use it. Finding an accurate, up-to-date sample frame is crucial to good sampling. Unfortunately, valid sample frames are difficult to find in many developing countries. Lack of a valid sample frame is a major source of error in sampling.

Statistic. A statistic is a finding based on a sample. All the results described for the Sudan Fertility Survey are statistics. Statistics are generally reported as percentages, averages, and measures of variation among scores.