What is the explicit meaning of the term sampling as applied in research?
Sampling, in research, is a term for the technique researchers use when they are selecting the participants for their study.
In order to conduct sampling, a researcher needs to first identify a population relevant to the study. This is the group of people who share some sort of demographic (i.e. high school students) that the researcher is making a hypothesis about and attempting to prove.
From the population, the researcher specifies a sampling frame, which is a specific group of people within the demographic that the samples will be drawn from (i.e. high school students in Detroit). The sampling frame typically doesn't include the entire population because that would be impossible, but it can still be pretty big. The sampling frame can also vary in size (i.e. high school students at one high school in Detroit, or high school students in Michigan). Although it is unlikely that a researcher will typically be able to study every single participant within the sampling frame, it gives her good parameters for the sampling process.
During sampling, it is crucial that researchers choose a sampling method, which can be random or non-random. Random works best if the sampling frame does not best represent the population as a whole, and the researcher wants to ensure that the demographic makeup of the sample better matches the demographic makeup of the population. Non-random works best if the demographic makeup of the sampling frame more or less parallels that of the population.
Using a sampling method within the sampling frame, researchers choose a sample. Typically, the bigger the sample size, the better, because then it is more representative of the entire population. However, it is vital to balance goals with resources!
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