What Does It Mean For A Sociologist To Control For A Variable

ii.two Stages in the Sociological Research Process

Learning Objectives

Listing the major stages of the sociological research process.
Describe the different types of units of analysis in sociology.
Explain the difference between an independent variable and a dependent variable.

Sociological research consists of several stages. The researcher must beginning choose a topic to investigate and so become familiar with prior research on the topic. Once appropriate information are gathered and analyzed, the researcher can then draw appropriate conclusions. This department discusses these various stages of the research process.

Choosing a Research Topic

The offset step in the enquiry process is choosing a topic. There are countless topics from which to choose, so how does a researcher go virtually choosing i? Many sociologists cull a topic based on a theoretical involvement they may have. For instance, Émile Durkheim's interest in the importance of social integration motivated his awe-inspiring study of suicide that Chapter i "Sociology and the Sociological Perspective" discussed. Many sociologists since the 1970s have had a theoretical interest in gender, and this interest has motivated a huge volume of research on the difference that gender makes for behavior, attitudes, and life chances. The link betwixt theory and research lies at the centre of the sociological enquiry process, as it does for other social, natural, and physical sciences. Accordingly, this book discusses many examples of studies motivated by sociologists' varied theoretical interests.

Many sociologists, such as the two pictured here, have a theoretical interest in gender that leads them to investigate the importance of gender for many aspects of the social globe.

Many sociologists also cull a topic based on a social policy involvement they may accept. For instance, sociologists concerned about poverty have investigated its effects on individuals' health, educational attainment, and other outcomes during childhood, adolescence, and machismo. Sociologists concerned virtually racial prejudice and discrimination have carried out many studies documenting their negative consequences for people of colour. As Chapter i "Sociology and the Sociological Perspective" discussed and as this volume emphasizes, the roots of sociology in the United states prevarication in the employ of sociological noesis to attain social reform, and many sociologists today continue to engage in numerous enquiry projects because of their social policy interests. The news story that began this chapter discussed an important example of this type of inquiry. The "Sociology Making a Difference" box further discusses research of this type.

Sociology Making a Departure

Survey Research to Help the Poor

The Customs Service Society (CSS) of New York Metropolis is a nonprofit organization that, according to its Web site (http://world wide web.cssny.org), "engages in advocacy, research and direct service" to help low-income residents of the urban center. It was established virtually 160 years agone and has made many notable accomplishments over the years, including aiding the victims of the Titanic disaster in 1912, helping initiate the free school lunch program that is at present institute effectually the United States, and establishing the largest senior volunteer program in the nation.

A key component of the CSS'southward efforts today involves gathering much information nigh the lives of poor New Yorkers through an annual survey of random samples of these residents. Because the needs of the poor are so often neglected and their voices so often unheard, the CSS calls this effort the Unheard Tertiary survey, as the poor correspond about one-tertiary of the New York City population. The Unheard 3rd survey asks respondents their opinions about many issues affecting their lives and also asks them many questions about such matters as their health and wellness care needs, employment status and task satisfaction, debt, and housing. The CSS then uses all this data in reports nigh the needs of the poor and nigh-poor in New York that information technology prepares for city and country officials, the news media, and fundamental individuals in the private sector. In these ways, the CSS uses survey research in the service of society. As its Web site (http://www.cssny.org/research) states, "research is a critical tool nosotros apply to increase our understanding of conditions that drive poverty as we abet for public policy and programs that will meliorate the economical continuing of low-income New Yorkers."

A third source of inspiration for research topics is personal experience. Like other social scientists (and probably as well natural and physical scientists), many sociologists accept had diverse experiences during childhood, adolescence, or adulthood that atomic number 82 them to study a topic from a sociological standpoint. For case, a sociologist whose parents divorced while the sociologist was in high school may become interested in studying the effects of divorce on children. A sociologist who was arrested during college for a political protestation may get interested in studying how effective protest might be for achieving the aims of a social movement. A sociologist who acted in high school plays may choose a dissertation during graduate school that focuses on a topic involving social interaction. Although the verbal number will never be known, many enquiry studies in sociology are undoubtedly first conceived because personal feel led the author to get interested in the theory or social policy addressed by the study.

Conducting a Literature Review

Whatever topic is chosen, the side by side phase in the research process is a review of the literature. A researcher who begins a new project typically reads a skillful number of studies that have already been published on the topic that the researcher wants to investigate. In sociology, most of these studies are published in journals, but many are also published as books. The government and private research organizations also publish reports that researchers consult for their literature reviews.

Regardless of the type of published study, a literature review has several goals. First, the researcher needs to determine that the study she or he has in mind has non already been washed. 2nd, the researcher needs to decide how the proposed study will add together to what is known near the topic of the study. How will the study add to theoretical knowledge of the topic? How will the report improve on the methodology of earlier studies? How will the study aid social policy related to the topic? Typically, a research project must answer at to the lowest degree one of these questions satisfactorily for it to have a run a risk of publication in a scholarly journal, and a thorough literature review is necessary to determine the new study's possible contribution. A tertiary goal of a literature review is to run across how prior studies were conducted. What enquiry design did they use? From where did their data come? How did they measure cardinal concepts and variables? A thorough literature review enhances the methodology of the researcher'southward new study and enables the researcher to correct whatsoever possible deficiencies in the methodology of prior studies.

In "the sometime days," researchers would conduct a literature review primarily by going to an academic library, consulting a printed index of bookish journals, trudging through shelf subsequently shelf of printed journals, and photocopying articles they establish or taking notes on index cards. Those days are long gone, and thankfully and so. At present researchers use any number of electronic indexes and read journal articles online or download a PDF version to read later. Literature reviews are withal a lot of work, but the time they take is immeasurably shorter than just a decade ago.

Formulating a Hypothesis

After the literature review has been completed, it is fourth dimension to codify the hypothesis that will guide the study. As you might think from a science class, a hypothesisA statement of the nature of the relationship between an independent variable and a dependent variable. is a argument of the relationship between ii variables apropos the units of analysis the researcher is studying. To understand this definition, we must next ascertain variable and unit of analysis. Allow'south start with unit of assayThe focus of sociological enquiry, ordinarily a person, organization, or geographical region. , which refers to the blazon of entity a researcher is studying. As nosotros discuss further in a moment, the most common unit of analysis in folklore is a person, but other units of analysis include organizations and geographical locations. A variableWhatever characteristic that varies among units of analysis. is whatsoever feature or gene that may differ amid the units of analysis that a researcher is studying. Fundamental variables in sociological studies of people as the units of analysis include gender, race and ethnicity, social class, age, and any number of attitudes and behaviors. Any unit of analysis is existence studied, sociological research aims to examination relationships between variables or, more precisely, to test whether 1 variable affects some other variable, and a hypothesis outlines the nature of the relationship that is to be tested.

Suppose we want to test the hypothesis that women were more than likely than men to have voted for Obama in 2008. The first variable in this hypothesis is gender, whether someone is a woman or a homo. (As Chapter xi "Gender and Gender Inequality" discusses, gender is actually more circuitous than this, but allow'south keep things simple for now.) The second variable is voting preference—for example, whether someone voted for Obama or McCain. In this case, gender is the independent variable and voting preference is the dependent variable. An independent variableA variable that affects the dependent variable. is a variable we think can affect another variable. This other variable is the dependent variableA variable that is influenced by an independent variable. , or the variable we retrieve is affected by the independent variable (see Figure 2.3 "Causal Path for the Independent and Dependent Variable"). When sociological research tests relationships between variables, it normally is testing whether an contained variable affects a dependent variable.

Figure 2.3 Causal Path for the Independent and Dependent Variable

Many hypotheses in folklore involve variables concerning people, just many also involve variables apropos organizations and geographical locations. As this statement is meant to suggest, sociological enquiry is conducted at different levels, depending on the unit of analysis chosen. As noted earlier, the most common unit of measurement of analysis in sociology is the person; this is probably the type of research with which yous are nearly familiar. If nosotros conduct a national poll to see how gender influences voting decisions or how race influences views on the state of the economy, we are studying characteristics, or variables, involving people, and the person is the unit of analysis. Another common unit of measurement of analysis in sociology is the organization. Suppose we conduct a written report of hospitals to run into whether the patient-to-nurse ratio (the number of patients divided by the number of nurses) is related to the average number of days that patients stay in the hospital. In this example, the patient-to-nurse ratio and the boilerplate number of days patients stay are both characteristics of the hospital, and the hospital is the unit of measurement of analysis. A third unit of analysis in sociology is the geographical location, whether information technology is cities, states, regions of a country, or whole societies. In the United States, for example, large cities generally accept higher violent offense rates than small-scale cities. In this case, the metropolis is the unit of measurement of assay.

Figure two.4

Ane of the units of analysis in sociological inquiry is the geographical location. The major regions of the United states of america are frequently compared on various characteristics. In ane notable finding, the South has the highest regional homicide charge per unit.

Measuring Variables and Gathering Data

After the hypothesis has been formulated, the sociologist is now ready to begin the actual research. Data must be gathered via one or more of the inquiry designs examined after in this affiliate, and variables must be measured. Data can either be quantitative (numerical) or qualitative (nonnumerical). Data gathered through a questionnaire are usually quantitative. The answers a respondent gives to a questionnaire are coded for computer analysis. For example, if a question asks whether respondents consider themselves to exist politically conservative, moderate, or liberal, those who answer "conservative" might receive a "ane" for reckoner analysis; those who cull "moderate" might receive a "2"; and those who say "liberal" might receive a "iii."

Data gathered through observation and/or intensive interviewing, research designs discussed after in this affiliate, are usually qualitative. If a researcher interviews college students at length to run across what they call back about dating violence and how seriously they regard it, the researcher may make uncomplicated comparisons, such as "most" of the interviewed students have dating violence very seriously, but without really statistically analyzing the in-depth responses from such a report. Instead, the goal is to make sense of what the researcher observes or of the in-depth statements that people provide to an interviewer then to relate the major findings to the hypothesis or topic the researcher is investigating.

The measurement of variables is a complex topic and lies far beyond the scope of this discussion. Suffice it to say that authentic measurement of variables is essential in whatever inquiry project. In a questionnaire, for example, a question should be worded conspicuously and unambiguously. Take the following question, which has appeared in national surveys: "Do you always potable more than yous think you should?" This question is probably meant to measure whether the respondent has an alcohol problem. Simply some respondents might answer yep to this question even if they simply accept a few drinks per yr if, for example, they come from a religious background that frowns on alcohol use; conversely, some respondents who drink far also much might reply no because they practise not recollect they drinkable too much. A researcher who interpreted a yes response from the former respondents equally an indicator of an alcohol problem or a no response from the latter respondents as an indicator of no alcohol problem would exist in fault.

As some other case, suppose a researcher hypothesizes that younger couples are happier than older couples. Instead of asking couples how happy they are through a questionnaire, the researcher decides to detect couples every bit they walk through a shopping mall. Some interesting questions of measurement arise in this study. First, how does the researcher know who is a couple? Second, how certain tin the researcher be of the approximate age of each person in the couple? The researcher might be able to distinguish people in their 20s or early 30s from those in their 50s and 60s, just age measurement beyond this gross comparing might oft be in fault. 3rd, how sure can the researcher be of the couple'due south degree of happiness? Is it really possible to determine how happy a couple is by watching them for a few moments in the mall? What exactly does being happy look similar, and exercise all people await this style when they are happy? These and other measurement problems in this particular study might be and then severe that the study should not be done, at least if the researcher hopes to publish it.

Sampling

After any measurement issues have been resolved, information technology is fourth dimension to gather the data. For the sake of simplicity, let's assume the unit of measurement of analysis is the person. A researcher who is doing a report "from scratch" must decide which people to report. Because it is certainly impossible to study everybody, the researcher but studies a sampleA subset of a population. , or subset of the population of people in whom the researcher is interested. Depending on the purpose of the study, the population of interest varies widely: it can exist the adult population of the United states of america, the adult population of a particular state or city, all immature women aged xiii–18 in the nation, or countless other variations.

Many researchers who practice survey research (discussed in a later on section) report people selected for a random sampleA subset drawn from the larger population in which every unit in the population has the same hazard of being included in the subset. of the population of interest. In a random sample, everyone in the population (whether it exist the whole U.S. population or just the population of a state or city, all the college students in a land or city or all the students at just i higher, and so forth) has the same chance of being included in the survey. The means in which random samples are chosen are too complex to fully discuss here, but suffice it to say the methods used to determine who is in the sample are equivalent to flipping a money or rolling some dice. The dazzler of a random sample is that information technology allows u.s.a. to generalize the results of the sample to the population from which the sample comes. This means that we tin be fairly sure of the attitudes of the whole U.S. population by knowing the attitudes of just 400 people randomly chosen from that population.

Other researchers use nonrandom samples, in which members of the population do not have the same chance of existence included in the study. If you ever filled out a questionnaire after being approached in a shopping mall or campus student center, information technology is very probable that you were part of a nonrandom sample. While the results of the written report (marketing inquiry or social science research) for which you were interviewed might take been interesting, they could not necessarily be generalized to all students or all people in a land or in the nation because the sample for the study was non random.

A specific type of nonrandom sample is the convenience sampleA nonrandom sample that is used because information technology is relatively quick and inexpensive to obtain. , which refers to a nonrandom sample that is used because it is relatively quick and cheap to obtain. If yous ever filled out a questionnaire during a high school or college class, as many students take done, you were very likely part of a convenience sample—a researcher can simply go into grade, hand out a survey, and have the data available for coding and analysis inside a few minutes. Convenience samples oft include students, simply they too include other kinds of people. When prisoners are studied, they constitute a convenience sample, because they are definitely non going anywhere. Partly because of this fact, convenience samples are besides sometimes called convict-audience samples.

Some other specific type of nonrandom sample is the quota sampleA nonrandom sample in which units in the sample are chosen according to one or more than characteristics so that the sample resembles these characteristics of the population as closely as possible. . In this type of sample, a researcher tries to ensure that the makeup of the sample resembles one or more characteristics of the population as closely as possible. For example, on a campus of ten,000 students where lx% of the students are women and 40% are men, a researcher might make up one's mind to study 100 students by handing out a questionnaire to those who happen to be in the student center building on a particular day. If the researcher decides to accept a quota sample based on gender, the researcher volition select 60 women students and 40 male person students to receive the questionnaire. This procedure might make the sample of 100 students more than representative of all the students on campus than if it were not used, but it notwithstanding does not make the sample entirely representative of all students. The students who happen to be in the student heart on a detail solar day might be very different in many respects from almost other students on the campus.

As we shall see later when research design is discussed, the choice of a design is very much related to the type of sample that is used. Surveys lend themselves to random samples, for example, while observation studies and experiments lend themselves to nonrandom samples.

Analyzing Data

Later on all data have been gathered, the next stage is to analyze the data. If the data are quantitative, the analysis will almost certainly use highly sophisticated statistical techniques beyond the scope of this give-and-take. Many statistical analysis software packages exist for this purpose, and sociologists learn to use 1 or more than of these packages during graduate school. If the data are qualitative, researchers analyze their data (what they have observed and/or what people have told them in interviews) in ways over again beyond our scope. Many researchers now use qualitative analysis software that helps them uncover important themes and patterns in the qualitative data they gather. However qualitative or quantitative data are analyzed, it is essential that the analysis exist equally accurate as possible. To become back to a point just made, this means that variable measurement must as well be as authentic as possible, because fifty-fifty good analysis of inaccurate data will yield inaccurate results. As a phrase from the field of computer science summarizes this trouble, "garbage in, garbage out." Information analysis can exist accurate only if the data are accurate to brainstorm with.

Criteria of Causality

As researchers analyze their information, they naturally try to decide whether their analysis supports their hypothesis. As noted above, when we test a hypothesis, we want to exist able to conclude that an contained variable affects a dependent variable. Four criteria must be satisfied earlier we can conclude this (see Table two.ane "Criteria of Causality").

Table 2.1 Criteria of Causality

ane. The contained variable and dependent variable must be statistically related.

2. The contained variable must precede the dependent variable in time and/or in logic.

3. The human relationship between the independent variable and dependent variable must non be spurious.

4. No amend explanation exists for the relationship between the contained variable and the dependent variable.

First, the independent variable and the dependent variable must be statistically related. That ways that the independent variable makes a statistical difference for where one ranks on the dependent variable. Suppose we hypothesize that age was related to voting preference in the 2008 presidential election. Hither historic period is clearly the independent variable and voting preference the dependent variable. (It is possible for age to affect voting preference, but it is non possible for voting preference to bear on age.) Leave poll information indicate that 66% of 18- to 24-yr-olds voted for Obama in 2008, while merely 45% of those 65 and older voted for him. The two variables are thus statistically related, every bit younger voters were more likely than older voters to prefer Obama.

The second criterion is called the causal society (or chicken-and-egg) problem and reflects the familiar proverb that "correlation does not mean causation." Just because an independent and a dependent variable are related does not automatically mean that the independent variable affects the dependent variable. It might well be that the dependent variable is affecting the contained. To satisfy this criterion, the researcher must exist sure that the contained variable precedes the dependent variable in time or in logic. In the example just discussed, age might touch on voting preference, but voting preference definitely cannot affect historic period. Nonetheless, causal order is non every bit clear in other hypotheses. For example, suppose nosotros find a statistical human relationship between marital happiness and task satisfaction: the more than happy people are in their marriage, the more satisfied they are with their jobs. Which makes more sense, that having a happy matrimony leads you to similar your job more than, or that beingness satisfied with your piece of work leads you to accept a happier wedlock? In this case, causal society is non very clear, and thus the 2nd criterion is difficult to satisfy.

The third benchmark involves spurious relationshipsA relationship between an independent variable and a dependent variable that exists only considering the furnishings of a third variable accept not been taken into business relationship. . A relationship between an contained variable and dependent variable is spurious if a third variable accounts for the relationship because it affects both the independent and dependent variables. Although this sounds a bit complicated, an case or two should brand it clear. If you did a survey of Americans xviii and older, you would notice that people who attend higher accept worse acne than people who practice not attend college. Does this mean that attending college causes worse acne? Certainly not. Yous would find this statistical relationship only because a third variable, age, affects both the likelihood of attending college and the likelihood of having acne: young people are more likely than older people to attend college, and also more likely—for very different reasons—to accept acne. Controlling for age makes it articulate that the original human relationship between attending college and having acne was spurious. Figure 2.5 "Diagram of a Spurious Relationship" diagrams this particular spurious relationship; notice that there is no causal pointer between the attention higher and having acne variables.

Figure two.v Diagram of a Spurious Human relationship

In another example, the more fire trucks at a fire, the more than damage the fire causes. Does that mean that burn trucks somehow make fires worse, equally the familiar saying "too many cooks spoil the goop" might propose? Of grade non! The third variable here is the intensity of the fire: the more intense the burn down, the more fire trucks answer to fight information technology, and the more than intense the fire, the more impairment it causes. The relationship between number of burn trucks and damage the fire causes is spurious.

The final criterion of causality is that our explanation for the relationship between the independent and dependent variables is the best caption. Even if the first 3 criteria are satisfied, that does not necessarily mean the ii variables are in fact related. For example, the U.Due south. crime rate dropped in the early 1980s, and in 1984 the reelection entrada of President Ronald Reagan took credit for this drop. This relationship satisfied the first iii criteria: the crime rate fell later on President Reagan took office in 1981, the drop in the crime charge per unit could non have affected the election of this president, and there was no apparent third variable that influenced both why Reagan was elected and why the criminal offense rate roughshod. However, social scientists pointed to another reason that accounted for the law-breaking rate decrease during the 1980s: a drop in the nascence rate some 15–20 years earlier, which led to a decrease during the early 1980s of the number of U.S. residents in the high-crime ages of 15–xxx (Steffensmeier & Harer, 1991).Steffensmeier, D., & Harer, M. D. (1991). Did crime rise or autumn during the Reagan presidency? The effects of an "aging" U.South. population on the nation's criminal offence rate. Journal of Research in Crime and Delinquency, 28(3), 330–359. The relationship between the ballot of Ronald Reagan and the crime rate drop was thus but a coincidence.

Drawing a Conclusion

In one case the data are analyzed, the researcher finally determines whether the data analysis supports the hypothesis that has been tested, taking into business relationship the criteria of causality just discussed. Whether or not the hypothesis is supported, the researcher (if writing for publication) typically also discusses what the results of the present inquiry imply for both prior and future studies on the topic. If the chief purpose of the project has been to exam or refine a particular theory, the conclusion will discuss the implications of the results for this theory. If the main purpose has been to test or advance social policy, the decision volition talk over the implications of the results for policy making relevant to the project's subject matter.

Key Takeaways

Several stages compose the sociological enquiry process. These stages include (a) choosing a research topic, (b) conducting a literature review, (c) measuring variables and gathering data, (d) analyzing data, and (e) drawing a conclusion.
Sociologists normally base their choice of a enquiry topic on one or more than of the following: (a) a theoretical interest, (b) a social policy involvement, and (c) ane or more personal experiences.
Accurate measurement of variables is essential for sound sociological enquiry. As a minimum, measures should be every bit clear and unambiguous as possible.

For Your Review

Consider the following question from a survey: "More often than not speaking, are yous very happy, somewhat happy, or not also happy?" Write a cursory essay in which you evaluate how well this question measures happiness.
Recollect of a personal experience you have had that lends itself to a possible research project. Write a brief essay in which you describe the experience and discuss the hypothesis that the research project based on the experience would address.