article · International Journal of Academic Research in Education
Conventional research typically divides sampling methods into probability and non-probability categories, based on random or non-random selection. However, this binary division has limitations and fails to adequately capture the full range of sampling procedures used with human participants. Many studies claim to use random sampling when true random selection has not occurred. To address this, sampling techniques can be categorised into true-random, quasi-random, and non-random approaches. Each method carries specific criteria and appropriate use cases. True-random sampling, where every population unit has an equal chance of selection, enables direct estimation of population characteristics. In contrast, quasi-random techniques allow only indirect estimation of these characteristics, while non-random sampling methods cannot be used to estimate population attributes either directly or indirectly.
Properly categorising how human subjects are recruited is essential for drawing accurate conclusions from research data. Misidentifying non-random procedures as random can lead to invalid claims about broader populations. Refining sampling classifications helps investigators select appropriate methodologies and ensures that conclusions drawn from sample data accurately reflect what can and cannot be mathematically inferred about the wider public.
The abstract does not indicate a commercialisation angle or application pathway, as it focuses entirely on the theoretical classification and methodology of research sampling techniques.
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The most commonly used sampling techniques in systematic investigations are probability and nonprobability methods. While probability sampling is based on the principle of a random selection of participants in a particular study, non-random selection is the basis of probability sampling. The random and non-random classifications appear to have some potential flaws and are insufficient to represent all sampling procedures involving human participants. Similarly, most authors believe that they use random sampling techniques, although, in reality, they do not use true random sampling. Therefore, the objective of this article is to highlight that sampling techniques can be characterized as true-random, quasi-random, or nonrandom, rather than merely random and non-random. Attempts have been made to show how inadequate random and non-random sampling methods are, the characteristics of true-random, quasi-random, and nonrandom sampling procedures, and when each sampling procedure is appropriate. Since each unit of the population is randomly selected and the chance of selecting the unit is equal, a real random sample is used to estimate the characteristics of the population directly from the sample. With quasi-random sampling, it is not possible to directly estimate population characteristics, but only indirectly. However, population characteristics cannot be directly or indirectly estimated by using non-random sampling techniques.
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DOI: 10.17985/ijare.1225214
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