Sampling is a crucial step in most types of research. Without unlimited time and resources, you cannot study or observe everybody in every setting. Recognising this, researchers rely on sampling, or the process of selecting a finite set of observations to draw conclusions about a larger whole. Researchers must exercise care in choosing a sample to ensure a representative group of research subjects. For qualitative research, the concerns are even greater because of issues related to sample size and selection processes.
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Most research studies rely on random samples to ensure that the subjects of a study are representative of the larger population. Most qualitative research, however, is purposeful. Instead of drawing a random sample, qualitative researchers base a sample on their judgment and the purpose of their study. For example, a qualitative researcher who wants to compare adults with extreme political views would not draw a random sample because people of extreme left- or right-wing views comprise only a small segment of the population. As an alternative, a researcher could interview a sample of members of two political organisations: one with a leftist orientation and one with right-wing views.
Small Sample Sizes
Sample sizes in qualitative research are much smaller than the samples studied in quantitative research. The reason for this lies in the descriptive, detailed information collected through interviews and participant observation. Matthew Miles and Michael Huberman, authors of "Qualitative Data Analysis," point out that many qualitative studies examine only a single case. However, the authors caution that single cases are "nested." A qualitative researcher in education may observe only a single classroom, but individual students are nested within classrooms, which are nested within schools.
Depth vs. Breadth
Because so much qualitative research involves in-depth description of certain phenomena, researchers often rely on small sample sizes, enabling them to observe and explore their subjects in depth. Research teams can draw a larger sample, making it more representative of the larger population. Doing so, however, may sacrifice the depth of the study for greater breadth. Researchers or teams planning qualitative work must carefully consider the purpose and rationale of their study before deciding on a sample size.
Miles and Huberman wrote that qualitative sampling is often "theory-driven," with subjects chosen based on a researcher's knowledge of the theoretical framework that informs the research. They cite as an example a study that examines how teachers serve as role models who socialise children. The sample may be small, involving only four classrooms. If a research team follows relevant theory, it may select teachers according to gender, ethnicity and other characteristics, such as how stern or nurturing a teacher is.
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