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Sampling theory is the study of relationships existing between a population and samples drawn from the population. Sampling theory describes two sampling domains. Probability and nonprobability. In probability sampling, the sample population is selected randomly and findings can be generalized to the target population. They include simple, random, systematic, and clustered. Nonprobability sampling does not involve randomization selection and sampling methods include convenience or accidental, quota, and volunteer (McNiff, Petrick, 2018).
An example would be a healthcare company has 50,000 employees at different locations. The company wishes to make certain amendment in the human resource policy. So, instead of surveying all 50,000 employees they take a sample from the larger population and this sample will represent the population. The survey now can be presented to the sample. From their responses, a decision can be made if they are happy or not with the new policy.
Generalizability is when researchers apply their research findings and conclusions of a sample population to the population at large. Generalizability is credible when the sample population is highly representative of the larger group as a whole.
McNiff, P., Petrick, M., Grand Canyon University (Ed). (2018). Nursing research: Understanding methods for best practice. Retrieved from https://lc.gcumedia.com/nrs433v/nursing-research-understanding-methods-for-best-practice/v1.1