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Sampling Procedures and Methods
There are two different types of sampling procedures--probability and nonprobability. Probability sampling methods ensure that there is a possibility for each person in a sample population to be selected, whereas nonprobability methods target specific individuals. Nonprobability sampling methods include the following:
- Purposive samples: to purposely select individuals to survey.
- Volunteer subjects: to ask for volunteers to survey.
- Haphazard sampling: to survey individuals who can be easily reached.
- Quota sampling: to select individuals based on a set quota. For example, if a census indicates that more than half of the population is female, then the sample will be adjusted accordingly.
Clearly, there can be an inherent bias in nonprobability methods. Therefore, according to Weisberg, Krosnick, and Bowen (1989), it is not surprising that most survey researchers prefer probability sampling methods. Some commonly used probability sampling methods for surveys are:
- Simple random sample: a sample is drawn randomly from a list of individuals in a population.
- Systematic selection procedure sample: a variant of a simple random sample in which a random number is chosen to select the first individual and so on from there.
- Stratified sample: dividing up the population into smaller groups, and randomly sampling from each group.
- Cluster sample: dividing up a population into smaller groups, and then only sampling from one of the groups. Cluster sampling is " according to Lee, Forthofer, and Lorimer (1989), is considered a more practical approach to surveys because it samples by groups or clusters of elements rather than by individual elements" (p. 12). It also reduces interview costs. However, Weisberg et. al (1989) said accuracy declines when using this sampling method.
- Multistage sampling: first, sampling a set of geographic areas. Then, sampling a subset of areas within those areas, and so on.
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