Why You Need to Identify a Population for Statistical Research

For virtually any statistical study of a population, you have to center your attention on a particular group of individuals (for example, a group of people, cities, animals, rock specimens, exam scores, and so on). For example:

  • What do Americans think about the president’s foreign policy?

  • What percentage of planted crops in Wisconsin did deer destroy last year?

  • What’s the prognosis for breast cancer patients taking a new experimental drug?

  • What percentage of all cereal boxes get filled according to specification?

In each of these examples, a question is posed. And in each case, you can identify a specific group of individuals being studied: the American people, all planted crops in Wisconsin, all breast cancer patients, and all cereal boxes that are being filled, respectively. The group of individuals you want to study in order to answer your research question is called a population. Populations, however, can be hard to define. In a good study, researchers define the population very clearly, whereas in a bad study, the population is poorly defined.

The question of whether babies sleep better with music is a good example of how difficult defining the population can be. Exactly how would you define a baby? Under three months old? Under a year? And do you want to study babies only in the United States, or all babies worldwide? The results may be different for older and younger babies, for American versus European versus African babies, and so on.

Many times, researchers want to study and make conclusions about a broad population, but in the end — to save time, money, or just because they don’t know any better — they study only a narrowly defined population. That shortcut can lead to big trouble when conclusions are drawn. For example, suppose a college professor wants to study how TV ads persuade consumers to buy products. Her study is based on a group of her own students who participated to get five points extra credit. This test group may be convenient, but her results can’t be generalized to any population beyond her own students, because no other population was represented in her study.

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