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Convenience sampling is also known as grab, opportunity, accidental or haphazard sampling. With this method, the researcher uses subjects that are easy to reach. As the name describes, the researcher chooses subjects because of convenience. Some examples of convenience sampling are when students use their classmates in a research study or a television reporter interviews people on the street.
In research methods, there are two primary classifications for sampling methods: nonprobability and probability. With probability sampling methods, all possible subjects out of a population have some chance of being included in the sample. Researchers can even calculate the mathematical probability of one of them being selected. They can also calculate sampling error, which is the degree to which the sample might differ from the actual population.
Convenience sampling is a nonprobability method. This means that subjects are chosen in a nonrandom manner, and some members of the population have no chance of being included. With nonprobability sampling, researchers have no way of calculating how well their sample represents the population as a whole. In general, probability sampling is considered to be more stringent and accurate than nonprobability sampling, but it is not always feasible.
When time or cost is a factor, some researchers might use convenience sampling. It is often used in pilot or exploratory studies when the researcher wants an inexpensive and quick way to discern whether further research is warranted. Many social science studies use convenience sampling with students, paid volunteers or clients.
Another method that is similar to convenience sampling is called snowball sampling. This is another nonprobability method, in which current participants refer or identify other possible subjects. Snowball sampling is often used when members of a particular population are difficult to find.
There are obvious benefits to convenience sampling. It usually is a quick and relatively cost-effective method of gathering data. Many researchers already have a pool of clients, patients, students, colleagues or friends they can utilize.
Random sampling, a probability method, is considered the gold standard for research. With random sampling, every member of the population has an equal chance of being selected, thus the sample is a good representation of the population. A convenience sample is not representative of the population, and the method is not as structured or rigorous as probability methods. Studies that utilize this method of sampling should be evaluated critically for possible bias and limits on generalization of the results.
Convenience Sampling Method
The popularity of convenience sampling among researchers is likely due to the straightforward approach of the method. Any willing members of any random group of people will sufficiently serve as a data pool. In addition, researchers using convenience sampling typically have more freedom to design their studies since they are not as bound by constraints of respondent selection criteria.
As a result of this freedom, studies using convenience sampling can take various forms. For example, in-person interviews, paper surveys, mail-in responses, online surveys and emailed questions are valid methods for collecting data. Suppose the researcher has disclosed all data collection means in the study and explained possible problems with the methodologies. In that case, nothing disallows researchers to employ a mixture of several methods. As a result, researchers can identify a source of possibly willing participants and start approaching them right away.
Since convenience sampling is a nonprobability method, researchers don’t have to vet groups before starting their work. Instead of starting with the task of identifying ways of locating specific subgroups, researchers can focus more on providing meaningful survey questions.
Researchers using convenience sampling also have to start early identifying ways that their data gathering methods could influence their results. But, again, tackling the subject head-on at the beginning of the study increases the odds of obtaining accurate data at the end of the survey that genuinely reflects the views of the people sampled.
Disadvantages of Convenience Sampling
As mentioned previously, convenience sampling is not the most accurate data collection form. Instead, probability sampling, data collected from a prescreened population group, provides the most accurate, and therefore the most valuable, results. Typically, taking a group of respondents’ opinions separately from demographic information creates better results. Results obtained with convenience sampling will always have a tinge of doubt associated with them.
Data integrity problems in results obtained from convenience sampling can originate from researcher bias. Researchers can exhibit bias when selecting participants since they experience the same limitations of perception influencing everyone else. The typical tendency is to gravitate toward candidates for the survey that possess traits that make the researcher feel comfortable. In other words, individuals conducting random surveys will likely approach and ask people that they see as most like themselves to participate.
Data dependency is another possible problem affecting the results of studies obtained with convenience sampling. Dependency occurs when the responses have some underlying connections unbeknownst to the researcher. For example, did the fact that it was “Take a Picture With Santa” day at the mall influence the number of respondents researchers approached that had small children in the home? These dependent connections are usually not as apparent as the example cited. Sometimes, they can hide out of sight of the researcher and destroy the reliability of the data produced from the study.
Other unknown variables that connect the respondents in ways that are not apparent to the researcher can also negatively affect the accuracy of the results. For instance, the unseen connections that influence where people shop, how they respond to mailed surveys, their online habits, and many other factors also influence how easy they are for researchers to find to participate in a study.
Convenience Sampling Pros and Cons
Convenience sampling is by far the most popular data collection method among researchers. However, the advantages of providing a low-cost way to start collecting data outweigh some of the problems resulting from its use. In addition, by analyzing how the data collection methods could have influenced the outcomes, the researcher can help mitigate any uneasiness with how they collected the data.
The pros of convenience sampling lie primarily with the ease with which researchers can get started collecting data. Without the cost and impediment of prequalifying a massive population, convenience sampling can allow researchers to investigate initial questions and determine if further investigation is warranted.
The cons of convenience sampling result from the ease with which a variety of factors can subtly corrupt the validity of the data. Connections among participants or other unnoticed influences can cause researchers to misinterpret results. Incorrect conclusions could lead to poor decision-making and resource allotment to help correct problems misunderstood due to erroneous study results.
Using convenience sampling by no means invalidates a study. On the contrary, it remains the most widely used way to build studies and perform research. However, to remedy the problems that can occur due to convenience sampling, researchers have to look for ways unobserved connections can influence their findings.
When researchers can identify and compensate for these influences, they can produce high-quality data that can somewhat stand the rigors of statistical analysis.