Chapter 7 "Sampling"

This is “Sampling”, chapter 7 from the book Sociological Inquiry Principles: Qualitative and Quantitative Methods (index.html) (v. 1.0). This book is licensed under a Creative Commons by-nc-sa 3.0 (http://creativecommons.org/licenses/by-nc-sa/ 3.0/) license. See the license for more details, but that basically means you can share this book as long as you credit the author (but see below), don't make money from it, and do make it available to everyone else under the same terms. This content was accessible as of December 29, 2012, and it was downloaded then by Andy Schmitz (http://lardbucket.org) in an effort to preserve the availability of this book. Normally, the author and publisher would be credited here. However, the publisher has asked for the customary Creative Commons attribution to the original publisher, authors, title, and book URI to be removed. Additionally, per the publisher's request, their name has been removed in some passages. More information is available on this project's attribution page (http://2012books.lardbucket.org/attribution.html?utm_source=header). For more information on the source of this book, or why it is available for free, please see the project's home page (http://2012books.lardbucket.org/). You can browse or download additional books there. i Chapter 7 Sampling Who or What? Remember back in Chapter 1 "Introduction" when we saw the cute photo of the babies hanging out together and one of them was wearing a green onesie? I mentioned there that if we were to conclude that all babies wore green based on the photo that we would have committed selective observation. In that example of informal observation, our sampling strategy (just observing the baby in green) was of course faulty, but we nevertheless would have engaged in sampling. Sampling has to do with selecting some subset of one’s group of interest (in this case, babies) and drawing conclusions from that subset. How we sample and who we sample shapes what sorts of conclusions we are able to draw. Ultimately, this chapter focuses on questions about the who or the what that you want to be able to make claims about in your research. In the following sections we’ll define sampling, discuss different types of sampling strategies, and consider how to judge the quality of samples as consumers of social scientific research. 166 Chapter 7 Sampling 7.1 Populations Versus Samples LEARNING OBJECTIVE 1. Understand the difference between populations and samples. When I teach research methods, my students are sometimes disheartened to discover that the research projects they complete during the course will not make it possible for them to make sweeping claims about “all” of whomever it is that they’re interested in studying. What they fail to realize, however, is that they are not alone. One of the most surprising and frustrating lessons research methods students learn is that there is a difference between one’s population of interest and one’s study sample. While there are certainly exceptions, more often than not a researcher’s population and her or his sample are not the same. In social scientific research, a population1 is the cluster of people, events, things, or other phenomena that you are most interested in; it is often the “who” or “what” that you want to be able to say something about at the end of your study. Populations in research may be rather large, such as “the American people,” but they are more typically a little less vague than that. For example, a large study for which the population of interest really is the American people will likely specify which American people, such as adults over the age of 18 or citizens or legal residents. A sample2, on the other hand, is the cluster of people or events, for example, from or about which you will actually gather data. Some sampling strategies allow researchers to make claims about populations that are much larger than their actually sample with a fair amount of confidence. Other sampling strategies are designed to allow researchers to make theoretical contributions rather than to make sweeping claims about large populations. We’ll discuss both types of strategies later in this chapter. 1. The group (be it people, events, etc.) that you want to be able to draw conclusions about at the end of your study. 2. The group (be it people, events, etc.) from which you actually collect data. 167 Chapter 7 Sampling As I’ve now said a couple of times, it is quite rare for a researcher to gather data from their entire population Figure 7.1 of interest. This might sound surprising or disappointing until you think about the kinds of research questions that sociologists typically ask. For example, let’s say we wish to answer the following research question: “How do men’s and women’s college experiences differ, and how are they similar?” Would you expect to be able to collect data from all college students across all nations from all historical time periods? Unless you plan to make answering this If a researcher plans to study how children’s books have research question your entire life’s work (and then changed over the last 50 years, some), I’m guessing your answer is a resounding no way. her population will include all So what to do? Does not having the time or resources to children’s books published in the gather data from every single person of interest mean last 50 years (as represented by the books on the shelves in this having to give up your research interest? Absolutely image). Her sample, however, will not. It just means having to make some hard choices be made up of a smaller selection about sampling, and then being honest with yourself of books from that population (as and your readers about the limitations of your study represented by the stack of books on the table). based on the sample from whom you were able to actually collect data. © Thinkstock Sampling3 is the process of selecting observations that will be analyzed for research purposes. Both qualitative and quantitative researchers use sampling techniques to help them identify the what or whom from which they will collect their observations. Because the goals of qualitative and quantitative research differ, however, so, too, do the sampling procedures of the researchers employing these methods. First, we examine sampling types and techniques used in qualitative research. After that, we’ll look at how sampling typically works in quantitative research. KEY TAKEAWAYS • A population is the group that is the main focus of a researcher’s interest; a sample is the group from whom the researcher actually collects data. • Populations and samples might be one and the same, but more often they are not. • Sampling involves selecting the observations that you will analyze. 3. The process of selecting observations that will be analyzed for research purposes. 7.1 Populations Versus Samples 168 Chapter 7 Sampling EXERCISES 1. Read through the methods section of a couple of scholarly articles describing empirical research. How do the authors talk about their populations and samples, if at all? What do the articles’ abstracts suggest in terms of whom conclusions are being drawn about? 2. Think of a research project you have envisioned conducting as you’ve read this text. Would your population and sample be one and the same, or would they differ somehow? Explain. 7.1 Populations Versus Samples 169 Chapter 7 Sampling 7.2 Sampling in Qualitative Research LEARNING OBJECTIVES 1. Define nonprobability sampling, and describe instances in which a researcher might choose a nonprobability sampling technique. 2. Describe the different types of nonprobability samples. Qualitative researchers typically make sampling choices that enable them to deepen understanding of whatever phenomenon it is that they are studying. In this section we’ll examine the strategies that qualitative researchers typically employ when sampling as well as the various types of samples that qualitative researchers are most likely to use in their work. Nonprobability Sampling Nonprobability sampling4 refers to sampling techniques for which a person’s (or event’s or researcher’s focus’s) likelihood of being selected for membership in the sample is unknown. Because we don’t know the likelihood of selection, we don’t know with nonprobability samples whether a sample represents a larger population or not. But that’s OK, because representing the population is not the goal with nonprobability samples. That said, the fact that nonprobability samples do not represent a larger population does not mean that they are drawn arbitrarily or without any specific purpose in mind (once again, that would mean committing one of the errors of informal inquiry discussed in Chapter 1 "Introduction"). In the following subsection, “Types of Nonprobability Samples,” we’ll take a closer look at the process of selecting research elements5 when drawing a nonprobability sample. But first, let’s consider why a researcher might choose to use a nonprobability sample. 4. Sampling techniques for which So when are nonprobability samples ideal? One instance might be when we’re a person’s likelihood of being designing a research project. For example, if we’re conducting survey research, we selected for membership in the may want to administer our survey to a few people who seem to resemble the folks sample is unknown. we’re interested in studying in order to help work out kinks in the survey. We 5. The individual unit that is the might also use a nonprobability sample at the early stages of a research project, if focus of a researcher’s we’re conducting a pilot study or some exploratory research.

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