Chapter 7: Sampling Techniques
If you have taken an introductory psychology or sociology class at a large university, probably you have been a participant in someone’s research. Social science researchers on college campuses have a luxury that researchers elsewhere may not share—they have access to many (presumably) willing and able human guinea pigs. But that luxury comes at the cost of sample representativeness. One study of top academic journals in psychology found that over two-thirds (68%) of participants in studies published by those journals were based on samples drawn in the United States (Arnett, 2008). Further, the study found that two-thirds of the work that derived from US samples published in the Journal of Personality and Social Psychology were based on samples made up entirely of American undergraduates taking psychology courses.
These findings certainly beg the question: what do we actually learn from social scientific studies and about whom do we learn it? That is exactly the concern raised by Henrich, Heine, and Norenzayan (2010), authors of the article “The Weirdest People in the World?” In their article, Henrich et al. point out that behavioural scientists very commonly make sweeping claims about human nature based on samples drawn only from WEIRD (Western, educated, industrialized, rich, and democratic) societies, and often based on even narrower samples, as is the case with many studies relying on samples drawn from college classrooms. As it turns out, many robust findings about the nature of human behaviour when it comes to fairness, cooperation, visual perception, trust, and other behaviours, are based on studies that excluded participants from outside the United States, and sometimes excluded anyone outside the college classroom (Begley, 2010). This raises questions about what we really know about human behaviour as opposed to U.S. resident or U.S. undergraduate behaviour. Of course, not all research findings are based on samples of WEIRD folks like college students. But even then, it would behoove us to pay attention to the population on which studies are based and the claims that are being made about to whom those studies apply.
In the preceding discussion, the concern is with researchers making claims about populations other than those from which their samples were drawn. A related, but slightly different, potential concern is sampling bias. Bias in sampling occurs when the elements selected for inclusion in a study do not represent the larger population from which they were drawn. For example, a poll conducted online by a newspaper asking for the public’s opinion about some local issue will certainly not represent the public since those without access to computers or the internet, those who do not read that paper’s website, and those who do not have the time or interest will not answer the question.
Another thing to keep in mind is that, just because a sample may be representative in all respects that a researcher thinks are relevant, there may be relevant aspects that didn’t occur to the researcher when she was drawing her sample. So how do you know when you can count on results that are being reported? While there might not be any magic or always-true rules you can apply, there are a couple of things you can keep in mind as you read the claims researchers make about their findings.
- First, remember that sample quality is determined only by the sample actually obtained, not by the sampling method itself. A researcher may set out to administer a survey to a representative sample by correctly employing a random selection technique, but if only a handful of the people sampled actually respond to the survey, the researcher will have to be very careful about the claims he can make about his survey findings.
- Second, researchers may be drawn to talking about implications of their findings as though they apply to some group other than the population actually sampled. Though this tendency is usually quite innocent, it is all too tempting a way to talk about findings; consumers of those findings have a responsibility to be attentive to this sort of (likely unintentional) bait and switch.
- Third, keep in mind that a sample that allows for comparisons of theoretically important concepts or variables is certainly better than one that does not allow for such comparisons. In a study based on a non-representative sample, for example, we can learn about the strength of our social theories by comparing relevant aspects of social processes.
Practice identifying what a study is comparing
At their core, questions about sample quality should address who has been sampled, how they were sampled, and for what purpose they were sampled. Being able to answer those questions will help you better understand, and more responsibly read, research results.