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# Sampling theory definition

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The sampling theory is created to determine the most precise technique to study data in nursing research. The sampling process entails the collection, survey, and interpretation of data gathered using sampling theory (Glaser, 2017). Population, intended population, sampling process, available population, sampling structure, and sampling formula are the key components of sampling theory. The sampling theory is based on the sampling plan, which is the procedure through which data in nursing research is obtained. The sampling strategy employs both probability and non-probability designs. As a result, the process of collecting samples is known as sampling, and the theory that encourages sampling is known as the sampling theory. Sampling theory is applied in much statistical research. For instance, the administration in a factory may wish to know the number of faulty needles that are produced inside a given facility. The sampling process investigates in 6 weeks by inspecting 20 needles daily at a specific time during the day (Glaser, 2017). Sampling theory is characterized by the general population which is all needles that are manufactured during the week while the needles that are inspected are the sample. This is a perfect example of sampling theory in a needle factory.

In conclusion, the sampling theory is essential in studying large data. Through sampling theory, nursing research is done efficiently as it involves extensive data (Glaser, 2017). When research is finalized, the success of a survey, which consists of the sampling theory, is measured through generalizability. It is the evaluation of the importance of findings of a study is to a larger group of samples. If the results of a data applied to the general population, the nursing research is known to have good generalizability. Therefore, good generalizability in nursing research is essential to study data accurately.

Reference

Glaser, B. (2017). Discovery of grounded theory: Strategies for qualitative research. London: Routledge.

May 10, 2023
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