Sampling and research share a symbiotic relation. If a research has to be supported with strong numbers, sampling has to come into existence and when there is sampling being done, it has to be researched-based. So, two of them need to be together to fulfill the major role of finding right numbers for right conclusion in research. Here are a few reasons why sampling is important in research:
Sampling serves the most common goal of survey: Sampling comes as the foremost and the most challenging part in the survey research. This is because of it fulfills the most common goal of survey, that is, to collect the data representative of a population, thereby giving stronger reasons to researcher on finding more facts to his research.
It reduces errors: The information gathered from the survey is then used by the researcher to generalise findings from a drawn sample, but within the limits of random error.
Gives an idea of correct size: There are several tested methods, offered by standard textbook authors and researchers, that help in calculating statistical measurements. This, in turn, gives an upper hand to researchers in determining the correct sample size.
Now, what is sample size? In uncomplicated terms, it can be defined as one of the four inter-related features of a study design giving an ability to influence certain things like the detection of significant differences, relationships or interactions etc.
These survey designs can be helpful as they try to minimise alpha error and beta error. While alpha error is finding a difference that does not actually exist in the population, beta error is failure to find a difference that actually exists in the population.
Now, the question is that despite constituting different models for sampling, it seems that much more improvement is required. Researchers, these days, are learning new experimental statistics from highly competent statisticians. Then, they are doing their best to apply the formulas for bringing out right calculation in their research.
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