2.4: Populations and Samples

Because social scientists want to make people’s lives better, they see what works on a small group of people, and then apply it to everyone. The small group of people is the sample, and “everyone” is the population.

Sample and Population

A sample is the small group of people that scientists test stuff on. We want at least 30 people in each group, so a study about two different ways to take notes should have at least 60 people in the sample. A population is the “everyone” that we want to apply the results to. Sometimes, “everyone” can be a pretty small group; if Dr. MO measured the GPA of one of her Research Methods classes, then the sample would be the class and the population could be students in all Research Methods classes at her he college. If you remember the vocabulary that you learned in the section about the Empirical Study step of the scientific method (in section 2.3.3), GPA would be the DV and the different types of note-taking would be the IV.

A sample is a concrete thing. You can open up a data file, and there’s the data from your sample. The sample will often include the exact number of participants that the research collected data from. This is often identified as N, so a study with 60 participants would be identify the number of participants by stating N=60. A population, on the other hand, is a more abstract idea. It refers to the set of all possible people, or all possible observations, that you want to draw conclusions about, and is generally much bigger than the sample. In an ideal world, the researcher would begin the study with a clear idea of what the population of interest is, since the process of designing a study and testing hypotheses about the data that it produces does depend on the population about which you want to make statements. However, that doesn’t always happen in practice: usually the researcher has a fairly vague idea of what the population is and designs the study as best he/she can on that basis.

Examples

In the example about note-taking from this chapter's prelude, the sample would be the class from which we got the data from, and the population would be the biggest group that they could represent. There’s often more than one possible population, but I might say all college students could be a good population for this sample. Try out Exercise \(\PageIndex{1}\) to see if you can identify the sample and the population:

Exercise \(\PageIndex{1}\)

Let’s say I want to know if there’s a relationship between how much time students study for their course and their current GPA. Imagine that I asked 100 of my Introduction to Psychology students this semester to complete a course workload estimator (such as the Course Workload Estimator provided by Rice University) and get their current GPA from my college's institutional research office. For this scenario:

1. Who is the Sample?
2. Who could be the population? In other words, what is the biggest group that this sample could represent?

Answer

1. Who is the Sample? 100 Introduction to Psychology students
2. Who could be the population? In other words, what is the biggest group that this sample could represent? There are many possible populations, but all Introduction to Psychology students could work, or all Introduction to Psychology students at my college might make sense, too.

Sometimes it’s easy to state the population of interest. In a typical a experiment, determining the population of interest is a bit more complicated. Suppose Dr. Navarro ran an experiment using 100 undergraduate students as participants. Her goal, as a cognitive scientist, is to try to learn something about how the mind works. So, which of the following would count as “the population”:

• All of the undergraduate psychology students her university in Australia?
• Undergraduate psychology students in general, anywhere in the world?
• Australians currently living?
• Australians of similar ages to my sample?
• Anyone currently alive?
• Any human being, past, present or future?
• Any biological organism with a sufficient degree of intelligence operating in a terrestrial environment?
• Any intelligent being?

Each of these defines a real group of mind-possessing entities, all of which might be of interest to me as a cognitive scientist, and it’s not at all clear which one ought to be the true population of interest. Maybe surprisingly for you, there's no "right" answer! Although some of the suggestions get a little vague, they all could potentially be a population that Dr. Navarro's sample represents. Irrespective of how the population is defined, the critical point is that the sample is a subset of the population. The goal of researchers is to use our knowledge of the sample to draw inferences about the properties of the population.

Exercise \(\PageIndex{1}\)

Actual drug use is much higher than drug arrests suggest, so you might want to measure how many people use marijuana. If you send out a survey asking about their drug use to everyone with a driver’s license in California, but only 30% fill it out:

1. Who is the Sample?
2. Who could be the population? In other words, what is the biggest group that this sample could represent?

Answer

Add texts here. Do not delete this text first.

1. Who is the Sample? 30% of Californians with driver's licenses
2. Who could be the population? In other words, what is the biggest group that this sample could represent? There are many possible populations, but Californians who have driver's licenses might make the most sense here.

This last example shows that sometimes our sample limits who we can generalize our results about, who could be our population.

In almost every situation of interest, what we have available to us as researchers is a sample of data. The data set available to us is finite, and incomplete. We can’t possibly get every person in the world to do our experiment. The next section discusses different ways to identify who from the population could be in our study as the sample.