Convenience Sampling: What Is Convenience Sampling?

The convenience sampling method is a non-probability sampling technique that draws data from respondents that are convenient for researchers to reach. Examples of convenience sampling include surveying friends and family, positioning yourself at a store entrance to conduct market research, or posting online surveys and questionnaires that people may fill out if they wish. Other names for convenience sampling include opportunity sampling, grab sampling, availability sampling, and accidental sampling.

Convenience sampling is one of the most affordable and brisk ways to conduct survey research and assemble data sets. However, this type of sampling is also prone to selection bias and, as a consequence, sampling errors. For more representative samples of a target population, many researchers opt for other techniques like stratified sampling, cluster sampling, or systematic sampling with random selection.

Several characteristics distinguish the convenience sampling method.

1. 1. A non-probability sampling method: Convenience sampling is designed to promote a rapid response rate and convenience for those gathering data. This limits its sampling frame to those in easy proximity to researchers or to self-selecting individuals who choose to fill out online surveys and questionnaires. This makes it different from probability sampling, which seeks respondents at random.
2. 2. Known for speed and relatively low costs: Convenience sampling requires less research design and fewer efforts to create a data set. This relatively loose methodology makes it relatively affordable and faster than other research methods.
3. 3. Can be subject to sampling bias: One of the key disadvantages of convenience sampling is that it over-represents people who are easy for a researcher to contact. Researchers may have better access to people who share the same demographics or live in the same geographical area. This diminishes the qualitative properties of convenience sampling.

Convenience sampling may appear in the following circumstances.

1. 1. Informal in-person surveys: Researchers use informal sampling to poll a population of interest to glean their opinions. This involves asking people who are readily available to answer questions, such as friends and family.
2. 2. Self-selecting online surveys: Researchers can also conveniently access people's opinions by posting online surveys and accepting the response of anyone who fills one out. The sampling method is also called voluntary response sampling.
3. 3. Self-selecting healthcare trials: People who volunteer for health studies represent a form of convenience sampling and voluntary response sampling. To produce scientifically valuable data, health researchers must actively seek members of all demographics to test treatments and medications. So while convenience sampling can informally occur in healthcare, the most renowned published studies use more exacting methods.
4. 4. Pilot studies: Convenience sampling also works in pilot testing programs where respondents self-select because they are interested in new products or services.

The stratified sampling technique, also known as stratified random sampling, is a data collection method that breaks a larger population into different strata (subgroups). The number of strata and the sample size of each stratum depends on the total number of respondents in a study. One way to use this probability sampling method is to break the entire population of a study into specific demographics. For instance, researchers can stratify a population by breaking it up by gender or age into non-overlapping groups.

By comparison, the convenience method is a far less purposive sampling method. Rather than deliberately create subsets to improve qualitative data, convenience sampling prioritizes the speed and ease of gathering data. This produces results faster and for less money than most stratified sampling endeavors do, but it comes with the risk of sampling bias.

Convenience sampling can be done quickly and with relatively little exertion. This is because the researcher only surveys respondents they can conveniently reach through direct proximity or the participants’ willingness to respond to surveys and questionnaires.

The major downside of convenience sampling is selection bias. The researcher's selection bias manifests via seeking respondents who are easy to reach. The respondents themselves represent selection bias because they are the type of people who are more likely to engage with online surveys or voluntary questionnaires. While this is helpful to researchers, it does not mean they are representative of the total population. In order to produce high-quality data, researchers must use truly random sampling techniques, or they must use a carefully designed system involving quota sampling or stratified sampling.

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