Random and non-random sampling processes are the two types of sampling procedures. Both of these procedures offer a variety of strategies, and researchers choose the one that best fits their needs. There may be several sampling procedures that appear to be appropriate for the inquiry. How does one come to the decision that this approach is the best fit for their research? The researchers use their understanding of sampling principles to determine the sample selection technique.
Strategies for selecting samples
According to Kemper and colleagues (2003), there are seven such principles:
Appropriate logically
The sampling approach should follow logically from the conceptual framework as well as the study's research questions. It must support and respond to the research questions, as well as be consistent with the conceptual framework.
The sample technique should be appropriate for the research's objectives and goals. If one sampling approach does not meet the study objectives, two procedures might be combined to obtain a suitable sample.
A comprehensive database
The sample should be able to compile a comprehensive database on the topic under investigation. The sample size should be sufficient to accurately represent the sampling frame or population from which the sample was obtained. A sample that is too small may not accurately reflect the population, while a sample that is too large may be difficult to manage. As a result, selecting the appropriate sample size is critical.
Clear conclusions
The sample should at the very least allow for unambiguous conclusions and plausible explanations to be drawn from the data. The sample size should, once again, be proportional to the population size. Inferences should be impartial and exact thanks to the sampling procedure. And you can only do this if you employ the proper sample approach and follow the right processes. We acquire more exact inferences as the sample size grows. Of course, populations are enormous, and there comes a point where expanding the sample size too much makes it difficult to gather data and draw conclusions.
Ethical
The sampling method must be moral. If the researcher does not keep personal information secret, data protection and confidentiality concerns may occur. In non-probability research, sample selection should be based on theoretical considerations rather than personal preferences.
Feasible
The sampling strategy should be practical. The researcher must ensure that the sample strategy is practical given the resources available.
Generalizable
The sample design should enable the researcher to apply/generalize the study's findings to different situations or groups. Generalizability is a key part of research, and your sample method may have a significant impact on it. The generalizability of research can be greatly improved by selecting the correct sample.
Practical
The sampling strategy should be as effective as possible. Because you don't want to become caught in the middle of your study with too much tension, you should think about practicality.
EDITOR'S SOURCE: Cvclue
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