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. LEARN ABOUT: Sampling Frame 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.

Types of random sampling