(6)ĭetermining the exact sample size necessary for a study usually requires extensive statistical calculations. Saiful, a clinical researcher, who states that a “sample size larger than 30 and less than 500 are appropriate for most research,” adding that sub-samples also require at least 30 observations when applicable. For in-depth qualitative studies, Abbie Griffin and John Hauser found that “20-30 in-depth interviews are necessary to uncover 90-95% of all customer needs for the product categories studied.” (5) Thus, the authors determined that a sample size of 30 respondents would provide a reasonable starting point. There are many different ways to determine an appropriate sample size. To see how this calculation was performed, visit.
In other words, approximately 1 in 3 random samples of ten patients would overlook the actual statistic of aggravation (1 out of every 10 patients). The probability that the sample failed to include an unsatisfied patient is calculated to be 35%. However, when performing data analysis, it is critical to consider the population represented by a study of only ten patients. A research budget permits only one focus group with 10 clinic patients, and all respondents report feeling satisfied with their visit. The medical clinic has one staff member known to aggravate 1 out of every 10 patients visiting. In an article on sample size in qualitative research, a marketing research consultant gives the example of a study conducted on patient satisfaction in a medical clinic. In an over-sized experiment, an unnecessary number of subjects are exposed to a potentially harmful treatment, or are denied a potentially beneficial one.” (3) Theoretical Case Study: Dangers of Small Sample Size An under-sized experiment exposes the subjects to potentially harmful treatments without advancing knowledge. In an experiment involving human or animal subjects, sample size is a pivotal issue for ethical reasons. As Russell Lenth from the University of Iowa explains, “An under-sized study can be a waste of resources for not having the capability to produce useful results, while an over-sized one uses more resources than are necessary. Sample size is also important for economic and ethical reasons. (1) For qualitative studies, where the goal is to “reduce the chances of discovery failure,” a large sample size broadens the range of possible data and forms a better picture for analysis.
A sufficiently large sample size is also necessary to produce results among variables that are significantly different. Most importantly, a large sample size is more representative of the population, limiting the influence of outliers or extreme observations. Obtaining a sample size that is appropriate in both regards is critical for many reasons. When conducting research, quality sampling may be characterized by the number and selection of subjects or observations.
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