Which of the following is an example of a nonrandom sampling method?
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. For this reason, there are two types of sampling: the random or probabilistic sample and the non-probabilistic one. In this case, we will talk in-depth about non-probability sampling. Keep reading! Show
Definition: 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. It is a less stringent method. This sampling method depends heavily on the expertise of the researchers. It is carried out by observation, and researchers use it widely for qualitative research. Non-probability sampling is a method in which not all population members have an equal chance of participating in the study, unlike probability sampling. Each member of the population has a known chance of being selected. 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). Researchers use this method in studies where it is impossible to draw random probability sampling due to time or cost considerations. Select your respondents Types of non-probability samplingHere are the types of non-probability sampling methods:
Convenience sampling is a non-probability sampling technique where samples are selected from the population only because they are conveniently available to the researcher. 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.
This non-probability sampling method is very similar to convenience sampling, with a slight variation. 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. 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.
Hypothetically consider, a researcher wants to study the career goals of male and female employees in an organization. There are 500 employees in the organization, also known as the population. To understand better about a population, the researcher will need only a sample, not the entire population. Further, the researcher is interested in particular strata within the population. Here is where quota sampling helps in dividing the population into strata or groups.
In the judgmental sampling method, researchers select the samples based purely on the researcher’s knowledge and credibility. In other words, researchers choose only those people who they deem fit to participate in the research study. 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. Thus, this research technique involves a high amount of ambiguity.
Snowball sampling helps researchers find a sample when they are difficult to locate. Researchers use this technique when the sample size is small and not easily available. This sampling system works like the referral program. Once the researchers find suitable subjects, he asks them for assistance to seek similar subjects to form a considerably good size sample. Non-probability sampling examplesHere are three simple examples of non-probability sampling to understand the subject better.
When to use non-probability sampling?
Advantages of non-probability samplingHere are the advantages of using the non-probability technique
Select your respondents Difference between non-probability sampling and probability sampling:
Sampling with QuestionPro AudienceWhy restrict yourself to a limited population when you can access 22 million+ survey respondents around the globe? Every day, QuestionPro Audience enables researchers to collect actionable insights from pre-screened and mobile-ready respondents. Don’t let your survey receive biased answers. Good survey results are derived when the sample represents the population. Now you know non-probability sampling is a great tool to extract information from a specific population. If you are a student or belong to a branch in which academic activities are developed, QuestionPro Audience is for you. LEARN MORE What are nonThe commonly used non-probability sampling methods include the following.. Convenience or haphazard sampling. ... . Volunteer sampling. ... . Judgement sampling. ... . Quota sampling. ... . Snowball or network sampling. ... . Crowdsourcing. ... . Web panels. ... . Advantages and disadvantages of non-probability sampling.. Which of the following is not an example of nonWhich of the following is NOT a type of non-probability sampling? Quota sampling.
Which of the following is an example of non Probablistic sampling?Examples of nonprobability sampling include: Convenience, haphazard or accidental sampling – members of the population are chosen based on their relative ease of access. To sample friends, co-workers, or shoppers at a single mall, are all examples of convenience sampling.
What is nonNon-random sampling is a sampling technique where the sample selection is based on factors other than just random chance. In other words, non-random sampling is biased in nature. Here, the sample will be selected based on the convenience, experience or judgment of the researcher.
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