An example of convenience sampling would be using student volunteers known to the researcher.Here are three simple examples of non-probability sampling to understand the subject better. Once the researchers find suitable subjects, he asks them for assistance to seek similar subjects to form a considerably good size sample. This sampling system works like the referral program. Researchers use this technique when the sample size is small and not easily available. Snowball sampling helps researchers find a sample when they are difficult to locate. Thus, this research technique involves a high amount of ambiguity. Judgmental or purposive sampling is not a scientific method of sampling, and the downside to this sampling technique is that the preconceived notions of a researcher can influence the results. In other words, researchers choose only those people who they deem fit to participate in the research study. In the judgmental sampling method, researchers select the samples based purely on the researcher’s knowledge and credibility. Here is where quota sampling helps in dividing the population into strata or groups. Further, the researcher is interested in particular strata within the population. To understand better about a population, the researcher will need only a sample, not the entire population. There are 500 employees in the organization, also known as the population. Hypothetically consider, a researcher wants to study the career goals of male and female employees in an organization. Consecutive sampling technique gives the researcher a chance to work with many topics and fine-tune his/her research by collecting results that have vital insights. Here, the researcher picks a single person or a group of a sample, conducts research over a period, analyzes the results, and then moves on to another subject or group if needed. This non-probability sampling method is very similar to convenience sampling, with a slight variation. It is one of the reasons why researchers rely on convenience sampling, which is the most common non-probability sampling method, because of its speed, cost-effectiveness, and ease of availability of the sample. But, in some research, the population is too large to examine and consider the entire population. Ideally, in research, it is good to test a sample that represents the population. Researchers choose these samples just because they are easy to recruit, and the researcher did not consider selecting a sample that represents the entire population. Here are the types of non-probability sampling methods:Ĭonvenience sampling is a non-probability sampling technique where samples are selected from the population only because they are conveniently available to the researcher. Select your respondents Types of non-probability sampling Researchers use this method in studies where it is impossible to draw random probability sampling due to time or cost considerations. Non-probability sampling is most useful for exploratory studies like a pilot survey (deploying a survey to a smaller sample compared to pre-determined sample size). Each member of the population has a known chance of being selected. Non-probability sampling is a method in which not all population members have an equal chance of participating in the study, unlike probability sampling. It is carried out by observation, and researchers use it widely for qualitative research. This sampling method depends heavily on the expertise of the researchers. Keep reading! What is non-probability sampling?ĭefinition: Non-probability sampling is defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. In this case, we will talk in-depth about non-probability sampling. For this reason, there are two types of sampling: the random or probabilistic sample and the non-probabilistic one. When we are going to do an investigation, and we need to collect data, we have to know the type of techniques we are going to use to be prepared.
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