In contrast to probability sampling, where the probability of every member is knowable, in nonprobability sampling, the probability of being selected is not known. Nonprobability sampling techniques are quite arbitrary. A population may be defined, but little effort is expended to ensure that the sample accurately represents the population. However, among other things, nonprobability samples are cheap and convenient. Three types of nonprobability sampling are haphazard sampling, purposive sampling, and quota sampling.
Haphazard sampling One common form of nonprobability sampling is haphazard sampling or “convenience” sampling. Haphazard sampling could be called a “take-them-where-you-find-them” method of obtaining participants. Thus, you would select a sample of students from your school in any way that is convenient. You might stand in front of the student union at 9 a.m., ask people who sit around you in your classes to participate, or visit a couple of fraternity and sorority houses. Unfortunately, such procedures are likely to Page 152introduce biases into the sample so that the sample may not be an accurate representation of the population of all students. Thus, if you selected your sample from students walking by the student union at 11 a.m., your sample excludes students who do not frequent this location, and it may also eliminate afternoon and evening students. At many colleges, this sample would differ from the population of all students by being younger, working fewer hours, and being more likely to belong to a fraternity or sorority. Sample biases such as these limit your ability to use your sample data to estimate the actual population values. Your results may not generalize to your intended population but instead may describe only the biased sample that you obtained.
Purposive sampling A second form of nonprobability sampling is purposive sampling. The purpose is to obtain a sample of people who meet some predetermined criterion. Sometimes at a large movie complex, you may see researchers asking customers to fill out a questionnaire about one or more movies. They are always doing purposive sampling. Instead of sampling anyone walking toward the theater, they take a look at each person to make sure that they fit some criterion—under the age of 30 or an adult with one or more children, for example. This is a good way to limit the sample to a certain group of people. However, it is not a probability sample.
Quota sampling A third form of nonprobability sampling is quota sampling. A researcher who uses this technique chooses a sample that reflects the numerical composition of various subgroups in the population. Thus, quota sampling is similar to the stratified sampling procedure previously described; however, random sampling does not occur when you use quota sampling. To illustrate, suppose you want to ensure that your sample of students includes 19% first-year students, 23% sophomores, 26% juniors, 22% seniors, and 10% graduate students because these are the percentages of the classes in the total population. A quota sampling technique would make sure you have these percentages, but you would still collect your data using haphazard techniques. If you did not get enough graduate students in front of the student union, perhaps you could go to a graduate class to complete the sample. Although quota sampling is a bit more sophisticated than haphazard sampling, the problem remains that no restrictions are placed on how individuals in the various subgroups are chosen. The sample does reflect the numerical composition of the whole population of interest, but respondents within each subgroup are selected in a haphazard manner. These techniques are summarized in Table 7.3.