Nonprobability sampling

Nonprobability sampling is a method of choosing people to participate in a survey that uses arbitrary methods to select those who are able to take part. The group chosen to participate is, therefore, not fully representative of all people, and the results of the survey will be biased and should not be used to make generalizations that accurately represent a larger population. However, nonprobability sampling is often easier and less expensive than other methods, thus making it very useful for getting overall feedback or a general idea of how people think about a particular subject. It is also the only way to choose participants when they must meet specific criteria to be part of the survey, such as driving a certain kind of car or being above a specific age.

Background

When discussing surveys, a sample refers to a small group of people who are chosen out of a larger group to participate in the survey. The sample of people who take part plays a key role in determining the outcome of the survey; therefore, researchers are very careful to use a method of choosing their sample that will provide the kind of results they need. There are two main methods used to choose a sample: probability sampling and nonprobability sampling.

Probability sampling is also known as random sampling. In this method, people are chosen to participate at random. Everyone in the larger population has the same chance of being chosen, and no one is excluded. This means that the likelihood of any specific person in the larger group being chosen to participate can be calculated; for instance, if the larger group has one hundred thousand people and one thousand people are selected to participate, each person has a one in one hundred chance of being chosen.

This type of sampling has several advantages. It is an objective method that eliminates the chance of any bias on the part of the researchers in choosing subjects. The random nature of the selection process and the fact that all possible participants have an equal chance of being chosen means that the results of the survey will be representative of the larger group. This also means the results of the survey will be free of bias and can be used to make generalizations or inferences about the larger group.

For example, if one hundred out of a larger group of one thousand people participate in the survey, and ten of them report that they do not like broccoli, the researchers can project that one hundred people in the original group of one thousand will not like broccoli and that if they surveyed ten thousand people, they would find that about one thousand of them do not like broccoli. This makes probability sampling valuable for determining specific results and establishing a hypothesis for future study. In contrast, nonprobability sampling is more biased and less objective, but it still has a valid place in research.

Overview

In nonprobability sampling, the members of the larger group do not all have the same chance of participating. There can be a number of reasons for this. For example, a news reporter who wants to know people’s reaction to a new tax imposed by a city council might interview people shopping in the downtown area. Choosing this location automatically limits participants to those who are in town and walking down the street at that specific time. It also excludes a large number of people who live in the city who are not present at that place and time.

The participants of a nonprobability sample are not chosen randomly to represent a specific percentage or segment of a larger population. Therefore, the results cannot necessarily be generalized to the larger group. However, nonprobability sampling is still used frequently because it is often easier and more practical to select a sample this way. It is also the only way to choose a sample that targets specific characteristics. For instance, if a researcher wanted to know what people thought about a particular movie, it would make more sense to interview people coming out of the theater where it is being shown than to randomly choose people from a larger group.

Surveying people coming out of a theater is an example of a form of nonprobability sampling known as convenience sampling. As the name implies, the researcher chooses the subjects who are the most accessible and easiest to reach. Posing survey questions to teammates, members of a social media group, or fans of a particular music group would all be examples of convenience sampling.

There are several variations of nonprobability sampling, including purposive sampling, snowball sampling, quota sampling, and self-selection sampling. Purposive sampling involves choosing participants to fulfill a specific need. It is sometimes called judgmental sampling. It is often used when people with specific experience or knowledge are needed for the survey, such as experts on vintage cars from the 1950s. In snowball sampling, participants are asked to recommend someone else who might be interested in participating. This type of sampling is often used when the participants need to meet specific requirements, such as being a new parent or having played football in high school. In quota sampling, researchers look for participants until a specific number or quota of people is reached. They might interview the first fifty people they find or make sure half the respondents are male and half are female. Like snowball sampling, quota sampling is often used when participants who meet specific criteria are needed. Self-selection sampling is when the participant is presented with one opportunity to participate or not and is solely responsible for the decision. Satisfaction surveys at the end of a customer service experience are an example of this type of survey, as are many traditional psychological experiments.

Researchers can increase the likelihood that nonprobability sampling will provide good results by using it in the circumstances that are most appropriate. Considering the possible ways the results could be biased and choosing a large and diverse pool of subjects can help minimize biased results. The results of any study conducted using nonprobability sampling should also clearly indicate the subject selection method so that those who review the survey results are aware of the potential for bias.

Bibliography

“Nonprobability Sampling.” St. Olaf College, wp.stolaf.edu/ir-e/nonprobability-sampling. Accessed 21 Jan. 2025.

“Non-Probability Sampling.” Statistics Canada, 9 Feb. 2021, www150.statcan.gc.ca/n1/edu/power-pouvoir/ch13/nonprob/5214898-eng.htm. Accessed 21 Jan. 2025.

“Non-Probability Sampling.” SurveyMonkey, www.surveymonkey.com/mp/non-probability-sampling. Accessed 21 Jan. 2025.

“Non-Probability Sampling Techniques.” University of Guelph, www.uoguelph.ca/hftm/non-probability-sampling-techniques. Accessed 21 Jan. 2025.

“What is Non-Probability Sampling? Everything You Need to Know.” Qualtrics, www.qualtrics.com/experience-management/research/non-probability-sampling. Accessed 21 Jan. 2025.