Definition of Nonprobability Sampling
Nonprobability Sampling is defined as the Sampling technique that does not meet the criteria of obtaining the probability of getting any particular sample for calculation. This is a sampling technique that needs to be utilized with caution. Nonprobability Sampling Techniques cannot be used at all to derive inference from the sample to the general population.
Probability methods are utilized for large-scale studies that are related to representativeness while Non-Probability Approaches are more suited for research that is in-depth and qualitative. Here, the focus is towards understanding complex social phenomena. Research shows that only one situation exists in which a Non-Probability Sample can be appropriate- If a person is only interested in the specific cases that have been studied, one does not need to derive a probability sample from similar cases.
Textbooks on Nonprobability Sampling
A complex sampling technique like Nonprobability Sampling needs to be handled with caution, so marketers need a thorough understanding through related textbooks. Some details of textbooks on Nonprobability Sampling are stated as follows:
- How It's Done: An Invitation to Social Research by Emily Adler and Roger Clark (Published by Cengage Learning – Year 2007).
- Exploring Marketing Research by William Zikmund and Barry Babin (Published by Cengage Learning – Year 2006).
Examples of Nonprobability Sampling
Example 1: An interesting example of Nonprobability Sampling can be its utilization in conducting a case study. Here, the research has its limitations to a single group, usually with a similar characteristic or of a tiny size. Such kind of work can be biased for generalizing on to other cases, but it may not be biased for understanding the one case that is studied.
Example 2: Another interesting example of Nonprobability Sampling can be its utilization in Judgmental Sampling. Here, the researcher opts for the sample based upon who they think can be appropriate regarding the study. This technique is utilized primarily when there is a limited quantity of people who have expertise within the field being researched. Such samples are biased due to the reason that prominent experts may differ from other, equally expert but less prominent individuals.
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