What is sampling?

Sampling approaches
Finding your sample

This blog post attempts to answer one of the fundamental questions of any research project, and one that confuses many a researcher, what is sampling? Why is it important for this research study? First let us be clear the first step within the realm of any social enquiry includes making decisions, which allows for the design and selection of a research sample that matches the focus of this study.

If you are more interested in finding out how many people you should interview, then click here, otherwise continue reading.

To achieve a good sample range, from an early stage you the researcher (undergrad, postgrad, PhD) need to be clear on what is your focus. It does not matter how big or small the population, decisions still need to be made. For example in the view of Ritchie, Lewis, & Elam (2003) even if a study involves very small populations or single case studies, then decisions still need to be made about people, settings or actions (p. 77). In the view of Creswell (2011) in qualitative inquiry the intent is not to “generalise a population but to develop an in-depth exploration of a central phenomenon” (p. 206). Again this “central phenomenon” is crucial to your focus. So any chosen sample must meet the criteria of this phenomenon and crucially it must be appropriate to your identified approach.

As you may be aware this blog is all about qualitative research so the two common approaches taken within this type of approach are; purposive sampling and snowball sampling. Both approaches are designed to help you find your sample and get access to your sample. I am intending to write about these in more detail but will quickly go over them for brevity at this point.

A popular strategic approach to the creation of an appropriate sample is the use purposive sampling (Ritchie et al., 2003). This is defined by Ritchie et al., (2003), as a strategy where “Members of a sample are chosen with a purpose to represent a location or type in relation to the criterion” (p. 77). The defining attributes of the purposive sampling strategy, which make it reasonable for this thesis as opposed to other methods such as the theoretical sample, is the ability to critically think and define the parameters of the population that is intended to be studied at an early stage (Miles & Huberman, 1994).

A complementary strategy to this, used to obtain richer level of depth and detail in the view of Ritchie et al., (2003), is the use of a snowballing strategy, which involves asking people who have already been interviewed to identify other people they know who fit the selection criteria (Crabtree & Miller, 1999; Groenewald, 2004). This approach allows you to utilise the original group as informants who can help in identifying additional people to interview who qualify for inclusion and these, in turn, identify yet others – hence the term snowball sampling (Cohen et al., 2007).

Just as a word of caution during the implementation of the sampling strategies outlined above Ritchie et al., (2003) recommend than when selecting a purposive sampling strategy, criteria should be carefully chosen that spans across areas such as demographics, characteristics, circumstances, experiences and attitudes. Thus in my view to keep your sample as wide as possible it may be a good idea to keep your criterion very simple, as is the view of Ritchie et al., (2003) who argue that complex criteria can affect the quality and range of the sample.

So as my graphic designer lecturer used to say KISS (Keep it simple stupid)

References

Crabtree, B. F., & Miller, W. L. (1999). Doing Qualitative Research. SAGE Publications. Retrieved from http://books.google.com/books?hl=en&lr=&id=MEd2AwAAQBAJ&pgis=1

Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Educational Research (Fourth., Vol. 4). Pearson. doi:10.1017/CBO9781107415324.004

Groenewald, T. (2004). A phenomenological research design illustrated.

Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook. Sage.

Ritchie, J., Lewis, J., & Elam, G. (2003). Designing and selecting samples. In J. Ritchie & J. Lewis (Eds.), Qualitative research practice: A guide for social science students and researchers (pp. 77–108). London: Sage.

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