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Non-Probability Sampling


Non-Probability Sampling


Non-Probability Sampling methods can be useful when descriptive comments about the sample itself are desired. They are quick, inexpensive, and convenient. There are also other circumstances, such as in applied social research, when it is unfeasible or impractical to conduct probability sampling. The following are the techniques to use 

Non-Probability sampling:


I.                   Convenience Sampling


A sample is selected from a readily available list like telephone directory, voters’ list; however do not follow random selection procedures. The researcher studies all sampling items which are most conveniently available. Most of the pilot tests and pre-tests use connivances sampling. This sampling is easy and less expensive compared with other methods.


II.                Purposive sampling

In this sampling, the researcher sample with a purpose in mind. And usually would have one or more specific predefined groups that the researcher is seeking. Purposive sampling can be very useful for situation where the researcher need to reach a target sample quickly and where samplings for proportionally is not the major concern. This sample method is considered desirable when the universe happens to be small and known characteristics.

III.             Quota sampling


The quota sampling method is the non-probabilistic analogue of stratified random sampling. However, it differs in how the units are selected. In Quota sampling the units are selected by the interviewers. This result in selection bias. Thus, quota sampling is often used by market researcher.


IV.             Volunteer sampling
This method is highly applicable when the sample has pleasant measurement procedures such that probability sampling methods cannot be used.


V.                Snowball Sampling


In snowball sampling, the researcher may begin by identifying someone who meets the criteria for inclusion in the selected research problems. The researcher then asks them to recommend others who they may know and also meet the set criteria. Although, this method would hardly lead to representative samples, there are times when it may be the best method available. The researcher begins the research with few respondents whom are known and available. This method of sampling is especially useful when members of universe cannot easily be located or hard to find by probabilistic procedures. An important bias in this sampling is that the more other who know a given person the more the likely the person is to be selected in the sample. 



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