3.5 Quantitative Research Methods
In this section, we take a closer look at quantitative research methods that are commonly used in social science research. Here you will learn more about surveys and experiments. In the next section, we’ll explore qualitative research methods, including ethnography, interviews, content analysis, and community-based action research.
Surveys
Do you strongly agree? Agree? Neither agree nor disagree? Disagree? Strongly disagree? If you’ve heard this before, you’ve probably completed your fair share of surveys. At some point, most people in the United States respond to some type of survey. The 2020 U.S. Census is an excellent example of a large-scale survey intended to gather sociological data. Since 1790, the United States has conducted a survey consisting of six questions to collect demographic data about the residents who live in the United States.
As a research method, a survey collects data from subjects who respond to a series of questions about behaviors and opinions, often in the form of a questionnaire or an interview. Surveys are one of the most widely used scientific research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.
Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a useful method for discovering how people feel, think, and act—or at least how they say they feel, think, and act. Surveys can track preferences (such as for presidential candidates) or reported individual behaviors (such as sleeping, driving, or texting habits). They can also be used to collect information such as employment status, income, and education levels. Not all surveys are considered sociological research. Many surveys people encounter focus on identifying marketing needs and strategies rather than testing a hypothesis or contributing to social science knowledge. Questions such as, “How many hot dogs do you eat in a month?” or “Were the staff helpful?” are not usually designed as scientific research.
A survey targets a specific population, people who are the focus of a study, such as college athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes. Most researchers choose to survey a small sector of the population, or a sample. A sample is a manageable number of subjects who represent a larger population. Survey data can be quantified, and researchers can analyze responses using statistics.
Numbers that are presented in the media are routinely assumed to be correct. However, we should think a bit more about the samples used in data collection and the strategies used to evaluate statistics. For example, if you were to hear that 90 percent of college students still use Facebook as their main source of social media, you would likely be pretty surprised. However, if you learned that the sample consisted of 10 college students, perhaps who are all in the same Facebook group, the findings might seem a bit less surprising and maybe not entirely representative of all college students. In this case, it is important to examine both the sample size and the response rate of your survey. Response rate refers to the percentage of surveys completed by respondents and returned to the researchers. For a survey to be valid, there must be an adequate response rate. Once surveys are returned, researchers can begin analyzing the data.
Sociologist Joel Best offers some suggestions to help us identify common mistakes when examining statistical data. In popular media, there are a few statistical blunders that lead to misconceptions about data (Best 2008). Misplaced decimal points, misleading graphs, careless calculations, and inaccurate translations of numbers are the main issues that lead to statistical mistakes. To avoid some of these issues, it’s important to be clear about the relationship between variables.
Researchers aim to understand the relationship between variables. Researchers look for ways to identify relationships like causation and correlation. Causation refers to a change in one variable that directly affects or causes another variable (I hiked 10 miles, and now my feet are tired). Correlation is when a change in one variable coincides with a change in another variable, but does not necessarily indicate causation. For more examples explaining causation and correction, check out the five-minute video in the next section, “Activity: A Closer Look at Causation and Correlation.”
Activity: A Closer Look at Causation and Correlation
Distinguishing between these concepts is a valuable skill. For example, does ice cream kill? Or is something else going on? Learn more about causation and correlation by watching the video in figure 3.4.
https://www.youtube.com/watch?v=VMUQSMFGBDo
Be sure to come back and answer these questions:
- What are some examples of correlations that do not indicate causation?
- How does the ability to distinguish between these concepts help us when we are analyzing data?
Experiments
One way researchers test social theories is by conducting an experiment. An experiment refers to the testing of a hypothesis under controlled conditions. This approach closely resembles the scientific method. Researchers select this approach when they want to focus on isolating variables. To do this, they create a controlled setting, a setting in which the researcher has complete control of factors associated with the study. Not all questions about social interaction and social life can be answered with this approach, but it helps us learn more about patterns in controlled environments.
As a research method, either type of sociological experiment is useful for testing “if-then” statements: if a particular thing happens (cause), then another particular thing will result (effect). To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables.
Typically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group, and the other is the control group. The experimental group is exposed to the independent variable(s), and the control group is not. To test the benefits of tutoring, for example, the sociologist might provide tutoring to the experimental group of students but not to the control group. Then both groups would be tested for differences in performance to see if tutoring affected the experimental group of students.
However, using controlled experiments can pose certain challenges. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would need to be somewhat artificial. For example, the test would not result in a grade that was reflected on the student’s permanent record.
Furthermore, if a researcher told the students they were going to be observed as part of a study on measuring the effectiveness of tutoring, the students might not behave naturally. This is called the Hawthorne effect—which occurs when people change their behavior because they know they are being watched as part of a study. The Hawthorne effect is unavoidable in some research studies because sociologists have to make the purpose of the study known. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985).
Although this approach closely resembles the scientific method, there are some limitations researchers need to consider. Experiments work best when research can be conducted in a controlled setting, but controlled settings may not accurately reflect the complexities of the real world. Another limitation to consider is that experimental research with human subjects often uses some level of deception to gather information. To avoid influencing the results of the experiment, participants may not be told of the true purpose of the study. It is important to follow ethical guidelines and have a post-participation debriefing during which researchers fully explain the experiment and offer subjects support as they work through the effects of deception.
Licenses and Attributions for Quantitative Research Methods
Open Content, Original
“Qualitative Research Methods” by Jennifer Puentes is licensed under CC BY 4.0.
Open Content, Shared Previously
Last two sentences of the first paragraph and paragraphs three and four in “Surveys” are from “2.2 Research Methods” by Tonja R. Conerly, Kathleen Holmes, Asha Lal Tamang, Introduction to Sociology 3e, OpenStax, which is licensed under CC BY 4.0. Edited for consistency and brevity.
The first sentence of the first paragraph, the first three sentences of the second paragraph and paragraphs two through four of “Experiments” are from “2.2 Research Methods” by Tonja R. Conerly, Kathleen Holmes, Asha Lal Tamang in Introduction to Sociology 3e, OpenStax, which is licensed under CC BY 4.0. Edited for consistency and brevity
“Correlation” and “experiment” definitions from “Ch. 2 Key Terms” by Heather Griffiths and Nathan Keirns, Introduction to Sociology 3e, OpenStax, is licensed under CC BY 4.0.
“Activity: Activity: A Closer Look at Causation and Correlation” by Jennifer Puentes is adapted from “How Ice Cream Kills! Correlation vs. Causation” by DecisionSkills, and is licensed CC BY 4.0. Modifications include introduction and questions.
All Rights Reserved Content
Figure 3.4. “How Ice Cream Kills! Correlation vs. Causation” by DecisionSkills is shared under the Standard YouTube License.
research methods that use numerical data; the social world and experiences are translated into numbers that can be examined mathematically through statistical analysis.
research methods that work with non-numerical data and attempt to understand the experiences of individuals and groups from their own perspectives. With qualitative approaches, researchers examine how groups participate in their own meaning making and development of culture.
the study of people in their environments to understand the meanings they give to their activities.
one-on-one conversations with participants designed to gather information about a particular topic.
a systematic approach to record and value information gleaned from secondary data as it relates to the study at hand.
a method of collecting data from subjects who respond to a series of questions about behaviors and opinions, often in the form of a questionnaire or an interview. Surveys are one of the most widely used scientific research methods.
a person’s wages or investment dividends. Earned on a regular basis.
an explanation for a phenomenon based on a conjecture about the relationship between the phenomenon and one or more causal factors.
any collection of at least two people who interact with some frequency and who share some sense of aligned identity.
a change in one variable that directly has an effect on or causes another variable.
when a change in one variable coincides with a change in another variable, but does not necessarily indicate causation
the testing of a hypothesis under controlled conditions.
a set of people who share similar status based on factors like wealth, income, education, family background, and occupation.
a category of identity that ascribes social, cultural, and political meaning and consequence to physical characteristics.