Range 300 words
Include in-text citations and peer-reviewed references in APA format
Integrate theory research and/or professional experience
Include specific examples and/or substantiating evidence from course readings and research
Stay on topic and address the course objectives
Provide a new thought idea or perspective.
Demonstrate critical thinking skills and application of Blooms Taxonomy [Blooms Taxonomy for distinctions of writing that are expected: 1. Knowledge 2. Comprehension 3. Applications 4.Analysis 5. Synthesis 6. Evaluation] Cite a workplace application or organizational example of what we are learning.
Add a new twist or interpretation on a reference perspective.
Use critical thinking about an idea/concept or comparison and contrast.
Question or challenge a principle/perspective with sound rationale
Demonstrate proper spelling grammar and scholarly tone
W6DQ1: How do research questions frame and guide studies?
W6DQ2: What type of research questions would lead to a qualitative study? To a quantitative one? How would the wording differ? Discuss these questions relative to your field of study.
W6DQ3: How does a researcher determine how many research questions and hypotheses are needed for a particular study? Do all research studies require hypotheses?
W6DQ4: Why might a hypothesis be inappropriate for a qualitative study?
W6DQ5:* Is a quantitative study that has a research question but no hypothesis weaker than one with a hypothesis? Why or why not?
W6DQ6: How are research questions different from survey and/or interview questions?
TRIANGULATION
Surveyors and sailors measure distances between objects by taking observations from multiple positions. By observing the object from several different angles or viewpoints the surveyors and sailors can obtain a good fix on an objects true location (see Figure 6.1). Social researchers employ a similar process of triangulation. In social research we build on the principle that we learn more by observing from multiple perspectives than by looking from only a single perspective.
Triangulation
The idea that looking at something from multiple points of view improves accuracy.
Social researchers use several types of triangulation (see Expansion Box 6.1 Example of Four Types of Triangulation). The most common type is triangulation of measure meaning that we take multiple measures of the same phenomena. For example you want to learn about a persons health. First you ask the person to complete a questionnaire with multiple-choice answers. Next you conduct an open-ended informal interview. You also ask a live-in partner/caregiver about the persons health. You interview the individuals physician and together examine his or her medical records and lab test results. Your confidence that you have an accurate picture grows from the multiple measures you used compared to relying on just one especially if each measure offers a similar picture. Differences you see among the measures stimulates questions as well.
figure 6.1 Triangulation: Observing from Different Viewpoints
expansion box 6.1 Example of Four Types of Triangulation
TOPIC
The amount of violence in popular American films
Measures: Create three quantitative measures of violence: the frequency (e.g. number of killings punches) intensity (e.g. volume and length of time screaming amount of pain shown in face or body movement) and level of explicit graphic display (e.g. showing a corpse with blood flowing amputated body parts close-ups of injury) in films.
Observers: Have five different people independently watch evaluate and record the forms and degrees of violence in a set of ten highly popular American films.
Theory: Compare how a feminist a functional and a symbolic interaction theory explains the forms causes and societal results of violence that is in popular films.
Method: Conduct a content analysis of a set of ten popular films as an experiment to measure the responses of experimental subjects to violence in each film to survey attitudes toward film violence among the movie-going public and to make field observations on audience behavior during and immediately after showing the films.
Triangulation of observers is a variation on the first type. In many studies we conduct interviews or are the lone observer of events and behavior. Any limitations of a single observer (e.g. lack of skill in an area a biased view on an issue inattention to certain details) become restrictions of the study. Multiple observers bring alternative perspectives backgrounds and social characteristics. They thereby reduce the limitations. For example two people interact with and observe the behavior of ten 5-year-old children at a child care center. One of the observers is a 60-year-old White male pediatrician with 25 years of experience working in a large city hospital. The other is a 31-year-old Hispanic female mother of two children who has 6 years of experience as an elementary school teacher in a small town. Each observer may notice and record different data. Combining what both see and experience will produce a fuller picture than relying on either one alone.
Triangulation of theory requires using multiple theoretical perspectives to plan a study or interpret the data. Each theoretical perspective has assumptions and concepts. They operate as a lens through which to view the social world. For example a study of work relations in a bank could use conflict theory with its emphasis on power differences and inequality. The study could highlight the pay and working condition inequalities based on positions of authority (e.g. manager versus teller). The study reveals relevant differences in social backgrounds: a middle-aged White male manager with an MBA and a young African American female teller with an associates degree. Next rational choice theory is applied to focus on decision-making and rational strategies individuals use to maximize personal benefits. This perspective highlights how the bank manager varies the time/effort he devotes to various customers depending on their loan or savings account size. It also presents a better picture of how the teller invests her time and energy differently with various supervisors depending on whether she believes they might help her get a promotion. Each perspective guides the study: It identifies relevant data provides a set of concepts and helps to interpret the meaning and significance of the data.
Triangulation of method mixes the qualitative and quantitative research approaches and data. Most researchers develop an expertise in one approach but the approaches have complementary strengths. A study that combines both tends to be richer and more comprehensive. Mixing them occurs in several ways:1 by using the approaches sequentially first one and then the other or by using them in parallel or simultaneously. In the study that opened this chapter Klinenberg mixed a statistical analysis of quantitative data on deaths with interviews and document analysis. (seeExample Box 6.1 A Multimethod Study on page 166).
QUALITATIVE AND QUANTITATIVE ORIENTATIONS TOWARD RESEARCH
In all research we strive to collect empirical data systematically and to examine data patterns so we can better understand and explain social life yet differences between research approaches can create miscommunication and misunderstandings. They are mutually intelligible; grasping both approaches and seeing how each complements the other simply takes more time and effort. Next we will look at some sources of differences.
A first difference originates in the nature of the data itself. Soft data (i.e. words sentences photos symbols) dictate qualitative research strategies and data collection techniques that differ from hard data (in the form of numbers) for which quantitative approaches are used. Such differences may make the tools for a quantitative study inappropriate or irrelevant for a qualitative study and vice versa.
Another difference between qualitative and quantitative research originates in principles about the research process and assumptions about social life. Qualitative and quantitative research principles give rise to different languages of research with different emphases. In a quantitative study we rely more on positivist principles and use a language of variables and hypotheses. Our emphasis is on precisely measuring variables and test hypotheses. In a qualitative study we rely more on the principles from interpretive or critical social science. We speak a language of cases and contexts and of cultural meaning. Our emphasis is on conducting detailed examinations of specific cases that arise in the natural flow of social life. Interestingly more female than male social researchers adopt the qualitative approach.2
example box 6.1 A Multimethod Study
Lee and Bean (2007) mixed quantitative and qualitative research approaches in a study of multiracial identity in the United States. They observed that social diversity has increased because of growing immigration since 1970 and for the first time in 2000 the United States census offered the option of classifying oneself as multiracial. The new diversity contrasts to the long history of single-race categories and a dominant White-Black dichotomous racial division. Lee and Bean asked whether multiracial people feel free or highly constrained when they pick a single racial-ethnic or multiracial identity. They also asked whether selecting a multiracial category on the census form is a symbolic action or a reflection of a persons multiracial daily existence. In the quantitative part of the study the authors statistically analyzed 2000 census data on the numbers and mixes of people who classified themselves as multiracial. In the qualitative part of the study they conducted forty-six in-depth semi-structured interviews with multiracial adults from northern and southern California. In the interviews Lee and Bean asked how and why a person chose to identify herself or himself as she or he did whether that identity changed over time or by context and about language use and other practices associated with race and ethnicity. They interviewed adults of various mixtures of Asian White Latino and Black races. Based on the interviews Lee and Bean found that multiracial Blacks were less likely to call themselves multiracial than people of other mixed race categories. This restriction is consistent with the U.S. historical pattern of the public identifying a person with only some Black heritage as being Black. Persons of mixed White and Asian or Latino or Latino-Asian heritage had more flexibility. Some mixed Asian-White or Latino-White people self-identified as White because of public perceptions and a narrow stereotypical definition of proper Asian or Latino appearance. Other White-Asian and White-Latino people said that they are proud of their mixed heritage even if it made little difference in their daily encounters. People did not stick with one label but claimed different racial-ethnic backgrounds in different situations. Pulling together the quantitative and qualitative findings Lee and Bean suggested that racial-ethnic group boundaries are fading faster for Latinos and Asians than for Blacks. They concluded that a new Black versus non-Black divide is emerging to replace the old White-Black division but that Blacks are still in a disadvantaged position relative to all racial categories.
A third difference between qualitative and quantitative research lies in what we try to accomplish in a study. The heart of good workwhether it is quantitative or qualitativeis a puzzle and an idea (Abbott 2003:xi). In all studies we try to solve a puzzle or answer a question but depending on the approach we do this in different ways. In the heat wave study that opened this chapter Klinenberg (2002) asked why so many people died. But he also asked how they died and why some categories of people were greatly affected but others were not. In a quantitative study we usually try to verify or falsify a relationship or hypothesis we already have in mind. We focus on an outcome or effect found across numerous cases. The test of a hypothesis may be more than a simple true or false answer; frequently it includes learning that a hypothesis is true for some cases or under certain conditions but not others. In the heat wave study Klinenberg asked whether a persons social class influenced an outcome: being likely to die during the heat wave. Using quantitative data he tested the relationship between class and death rate by comparing the social class of the roughly 700 who died with thousands who did not.
In many qualitative studies we often generate new hypotheses and describe details of the causal mechanism or process for a narrow set of cases. Returning to the heat wave study Klinenberg (2002) tested existing hypotheses about class and death rates. He also developed several new hypotheses as he looked closely into the mechanism that caused some to die but not others. He learned that high death rates occurred in poverty- and crime-ridden neighborhoods. More males than females died and more African Americans died than Latinos or Whites. By walking around in different low-income neighborhoods and interviewing many people firsthand he identified the mechanisms of urban isolation that accounted for very different heat wave survival rates among people of the same social class. He examined the social situations of older African American men and discovered the local social environment to be the critical causal mechanism. He also looked at larger forces that created the social situations and local environments in Chicago in the mid-1990s.
A fourth difference between quantitative and qualitative studies is that each has a distinct logic and path of conducting research. In a quantitative study we employ a logic that is systematic and follows a linear research path. In a qualitative study the logic arises from ongoing practice and we follow a nonlinear research path. In the next section we examine the logics and paths of research.
Reconstructed Logic and Logic in Practice
How we learn and discuss research tends to follow one of two logics.3 The logics summarize the degree to which our research strategy is explicit codified and standardized. In specific studies we often mix the two logics but the proportion of each varies widely by study.
A reconstructed logic emphasizes using an explicit research process. Reconstructed logic has been reconstructed or restated from the many messy details of doing a real-life study into an idealized formal set of steps with standard practices and consistent principles terms and rules. You can think of it as a cleansed model of how best to do a high-quality study. Following this logic is like cooking by exactly following a printed recipe. Thus the way to conduct a simple random sample (discussed in Chapter 7) is straightforward and follows a clear step-by-step procedure.
Reconstructed logic
A logic of research based on reorganizing standardizing and codifying research knowledge and practices into explicit rules formal procedures and techniques; it is characteristic of quantitative research.
The logic in practice is messy and closer to the concrete practice of doing research. Logic in practice includes advice that comes from the practical activities of doing specific real-life studies more than a set of restated ideal rules. This logic relies heavily on judgment calls and tricks of the trade that active experienced researchers share. We learn it best by reading many studies and being an apprentice researcher and from the folk wisdom that passes informally among experienced researchers. It is like cooking without a written recipeadding a pinch of an ingredient here stirring until something looks right and adjusting while cooking until we reach a certain smell or taste.
Logic in practice
A logic of research based on an apprenticeship model and the sharing of implicit knowledge about practical concerns and specific experiences; it is characteristic of qualitative research.
You can see the reconstructed logic in the distinct research methods section of a quantitative research report. In contrast in qualitative research reports you may not see the research method (common for historical-comparative research) discussed or find it mixed with a personal autobiographical account of a particular study (common for field research). The absence of a standard method does not make qualitative study less valid; however it often requires more time and a different style of thinking for the newcomer to master.
Linear and Nonlinear Paths
The path is a metaphor for a sequence of things to do: what you finish first or where you have been and what comes next. You can follow a straight well-worn and marked path that has clear signposts and is where many others have trod before. Alternatively you may follow a path that meanders into unknown territory where few others have gone. The path has few signs so you move forward veer off to the side and sometimes backtrack a little before going forward again.
When using the linear research path we follow a fixed sequence of steps that are like a staircase that leads upward in one direction. By following a linear path we move in a direct narrow and straight way toward a conclusion. This pathway toward task completion is the dominant approach in western European and North American cultures. It is most widely used in quantitative research. By contrast a nonlinear research path requires us to make successive passes through the steps. We may move forward backward and sideways before advancing again. It is more of a spiral than a straight staircase. We move upward but slowly and indirectly. With each cycle or repetition we may collect new data and gain new insights.
Nonlinear research path
Research that proceeds in a cyclical iterative or back-and-forth pattern and is often used in qualitative research.
Linear research path
Research that proceeds in a clear logical step-by-step straight line; often used in quantitative research.
People who are accustomed to a direct linear approach often become impatient with a less direct cyclical path. Although a nonlinear path is not disorganized undefined chaos the cyclical path appears inefficient and without rigor. People who are used to a nonlinear path often feel stifled and boxed in by a linear approach. To them a linear path feels artificial or rigid. They believe that this approach prevents them from being naturally creative and spontaneous.
Each path has its strengths. The linear path is logical easy to follow and efficient. The nonlinear path can be highly effective in creating an authentic feeling for understanding an entire setting for grasping subtle shades of meaning for integrating divergent bits of information and for switching perspectives. Each path has its own discipline and rigor. The linear path borrows from the natural sciences with their emphasis on logic and precision. A nonlinear path borrows devices from the humanities (e.g. metaphor analogy theme motif and irony) and is suited for tasks such as translating languages a process in which delicate shades of meaning subtle connotations or contextual distinctions can be important (see Figure 6.2 for a graphic representation of each path).
Objectivity and Integrity
We try to be fair honest truthful and unbiased in our research activity yet we also have opportunities to be biased dishonest or unethical in all knowledge production including social research. The two major research approaches address the issue of reducing difficulties and ensuring honest truthful studies in different ways.
In qualitative research we often try to acquire intimate firsthand knowledge of the research setting. Thus we do not want to distance ourselves from the people or events we are studying. Acquiring an intimate understanding of a setting does not mean that we can arbitrarily interject personal opinion be sloppy about data collection or use evidence selectively to support our prejudices. Rather we take maximum advantage of personal insight inner feelings and life perspective to understand social life. We walk a fine line between intimacy and detachment and place personal integrity and honesty at the forefront. Some techniques may help us walk a fine line. One technique is to become highly sensitive to our own views preconceptions and prior assumptions and then bracket them or put them aside so we can see beyond them better. Instead of trying to bury or deny our assumptions viewpoints and values we find that acknowledging them and being open about them is best. We can then recognize how they might influence us. We try to be forthright and candid in our involvement in the research setting in dealing with the people in the study and with any relevant issues that arise. We do this in the way that we conduct the study and report on the findings.
Personal openness and integrity by the individual researcher are central to a qualitative study. By contrast in a quantitative study we stress neutrality and objectivity. In a quantitative study we rely on the principle of replication adhere to standardized procedures measure with numbers and analyze the data with statistics.4 In a sense we try to minimize or eliminate the subjective human factor in a quantitative study. As Porter (1995:7 74) has argued
Ideally expertise should be mechanized and objectified grounded in specific techniques. This ideal of objectivity is a political as well as scientific one. Objectivity means rule of law not of men. It implies the subordination of personal interests and prejudices to public standards.
figure 6.2 Graphic Representation of Linear and Nonlinear Paths
The issue of integrity in quantitative research mirrors the natural science approach. It relies on using an explicit and objective technology such as making statements in precise neutral terms using well-documented standard techniques and making replicable objective numerical measures.
Quantitative social research shares the hallmarks of natural science validation: explicit standard procedures; precise numerical measurement; and replication. By contrast validation in qualitative research relies more on a dependable credible researcher and her or his personal integrity self-discipline and trustworthiness.5 Four other forms of validation in qualitative research somewhat parallel the objective procedures found in quantitative studies.6
The first form indicates that the researcher has carefully evaluated various forms of evidence and checked them for consistency. For example a field researcher listens to and records a student who says Professor Smith threw an eraser at Professor Jones. The researcher must consider the evidence carefully. This includes considering what other people say about the event. The field researcher also looks for confirming evidence and checks for internal consistency. The researcher asks whether the student has firsthand knowledge of the event that is directly witnessed it and asks whether the students feelings or self-interest might lead him or her to lie (e.g. the student dislikes Professor Smith).
A second form of validation arises from the great volume of detailed written notes in most qualitative studies. In addition to verbatim description of the evidence other documentation includes references to sources commentaries by the researcher and quotes photographs videos maps diagrams paraphrasing and counts. The huge volume of information its great diversity and its interlocking and mutually reinforcing presentation help to validate its authenticity.
A third kind of validation comes from other observers. Most qualitative researchers work alone but many others know about the evidence. For example we study people in a specific setting who are alive today. Other researchers can visit the same setting and talk to the same people. The people we studied can read study details and verify or raise questions about it. Likewise historical-comparative researchers cite historical documents archival sources or visual material. By leaving a careful audit trail with precise citations others can check the references and verify sources.
A fourth type of truthfulness is created by the way we publicly disclose results. In a quantitative study we adhere to a standard format for writing a research report. We explain in detail how we followed accepted procedures. We describe each step of the study display the quantitative data in charts graphs or tables and make data files available to others to reanalyze. We offer to answer any questions about the study. In a qualitative study we cannot publicly display or share the many mountains of detailed notes recorded interviews photos or original source materials in a research report. They might fill an entire room! Instead we spin a web of interlocking details and use tightly cross-referenced material. Through our writing and presentation we provide sufficient texture and detail to build an I-was-there sense within readers. By providing rich specific descriptions supplemented with maps photos and verbatim quotations we convey an intimate knowledge of a setting. We build a sense of shared familiarity in readers. A skilled qualitative researcher can recreate the visual images voices smells sounds tensions and entire atmosphere that existed by referring to the mountains of empirical evidence.
Preplanned and Emergent Research Questions
Studies start in many ways but the usual first step is to select a topic.7 We have no formula for how to do this task. Whether we have experience or are just a beginning researcher the best guide is to pick something that interests us. There are many ways to select topics (see Expansion Box 6.2 Sources of Topics). We may begin with one topic but it is too large and is only a starting point. We must narrow it into a focused research question. How we do this varies by whether our study is primarily qualitative or quantitative. Both kinds of studies work well with some topics; we can study poverty by examining official statistics conducting a survey doing ethnographic field research or completing a historical-comparative analysis. Some topics are best suited for a qualitative study (e.g. how do people reshape their self-identity through participating in goth youth subculture) and others for a quantitative study (e.g. how has public opinion on the death penalty shifted over the past 50 years and whether ones opinion on this issue is influenced by views on related issues or by the amount of exposure the news media gives to certain topics).
Most qualitative studies start with a vague or loosely defined topic. The specific topic emerges slowly during the study and it may change direction based on new evidence. This was the case for Venkateshs study (2008) that opened Chapter 5. He began with an interest in studying poverty in an inner-city housing project but shifted to studying a drug-selling gang. Focusing on a specific research question continues while we gather data. Venkatesh increasingly focused his topic of gang activity into sharper questions: How and why did gangs in a low-income housing project sustain an underground economy and provide housing project residents with protection and aid services?
Flexibility in qualitative research encourages us to continuously focus throughout a study. An emergent research question may become clear only during the research process. We can focus and refine the research question after we gather some data and begin a preliminary analysis. In many qualitative studies the most important issues and most interesting questions become clear only after we become immersed in the data. We need to remain open to unanticipated ideas data and issues. We should periodically reevaluate our focus early in a study and be ready to change direction and follow new lines of evidence. At the same time we must exercise self-restraint and discipline. If we constantly change the focus of our research without end we will never complete a study. As with most things a balance is required.
expansion box 6.2 Sources of Topics
1. Personal experience. You can choose a topic based on something that happens to you or those you know. For example while you work a summer job at a factory the local union calls a strike. You do not have strong feelings either way but you are forced to choose sides. You notice that tensions rise. Both management and labor become hostile toward each other. This experience suggests unions or organized labor as a topic.
2. Curiosity based on something in the media. Sometimes you read a newspaper or magazine article or see a television program that leaves you with questions. What you read raises questions or suggests replicating what others research found. For example you read aNewsweek article on people who are homeless but you do not really know much about who they are why they are homeless whether this has always been a problem and so forth. This suggests homeless people as a topic.
3. The state of knowledge in a field. Basic research is driven by new research findings and theories that push at the frontiers of knowledge. As theoretical explanations are elaborated and expanded certain issues or questions need to be answered for the field to move forward. As such issues are identified and studied knowledge advances. For example you read about attitudes toward capital punishment and realize that most research points to an underlying belief in the innate wickedness of criminals among capital punishment supporters. You notice that no one has yet examined whether people who belong to certain religious groups that teach such a belief in wickedness support capital punishment nor has anyone mapped the geographic location of these religious groups. Your knowledge of the field suggests a topic for a research project: beliefs about capital punishment and religion in different regions.
4. Solving a problem. Applied research topics often begin with a problem that needs a solution. For example as part of your job as a dorm counselor you want to help college freshmen establish friendships with each other. Your problem suggests friendship formation among new college students as a topic.
5. Social premiums. This is a term suggested by Singleton and colleagues (1988:68). It means that some topics are hot or offer an opportunity. For example you read that a lot of money is available to conduct research on nursing homes but few people are interested in doing so. Your need of a job suggests nursing homes as a topic.
6. Personal values. Some people are highly committed to a set of religious political or social values. For example you are strongly committed to racial equality and become morally outraged whenever you hear about racial discrimination. Your strong personal belief suggests racial discrimination as a topic.
7. Everyday life. Potential topics can be found throughout everyday life in old sayings novels songs statistics and what others say (especially those who disagree with you). For example you hear that the home court advantage is very important in basketball. This statement suggests home court advantage as a topic for research.
Typical qualitative research questions include these: How did a certain condition or social situation originate? How do people events and conditions sustain a situation over time? By what processes does the situation change develop or end? Another type of question seeks to confirm existing beliefs or assumptions (e.g. do Southern and Northern Whites act differently around people of other races as those in McDermotts [2006] study of working class neighborhoods in Atlanta and Boston). A last type of research question tries to discover new ideas.8
In a quantitative study we narrow a topic into a focused question as a discrete planning step before we finalize the study design. Focusing the question is a step in the process of developing a testable hypothesis (to be discussed later). It guides the study design before you collect any data.9
In a qualitative study we can use the data to help narrow the focus. In a quantitative study we must focus without the benefit of data and use other techniques. After picking a topic we ask ourselves: What is it about the topic that is of greatest interest? For a topic about which we know little we must first acquire background knowledge by reading studies about the topic. Reading the research literature can stimulate many ideas for how to focus a research question.
In most quantitative studies research questions refer to relationships among a small number of variables. This means that we should list variables as we try to focus the topic into a research question (see Expansion Box 6.3 Techniques for Narrowing a Topic into a Research Question). For example the question what causes divorce? is not a good research question. A better one is is age at marriage associated with divorce? The second question has two variables: age of marriage and whether or not a divorce occurred (also see Example Box 6.2 Examples of Bad and Good Research Questions).
Personal experience can suggest topics. Perhaps personal experience suggests people released from prison as a topic as it did for Pager (2007). We can read about former inmates and their reentry and about probation in dozens of books and hundreds of articles. A focused research question might be whether it is more difficult for someone who has a nonviolent criminal record to get a job offer than someone without a criminal record. This question is more specific in terms of type of criminal record and the specific outcome for a former prisoner. It focuses on two variables whether a person has a criminal record and whether the person gets a job offer. A common type of research question asks which factor among several had the most significant impact on an outcome. We might ask as Pager did how does racial category (Black versus White) and whether a person had a criminal record affect the chances of getting a job? Did race make a difference did being a former prisoner make a difference did the two factors operate separately cancel out one another or intensify one another in their impact on getting a job offer?
expansion box 6.3 Techniques for Narrowing a Topic into a Research Question
1. Examine the literature. Published articles are excellent sources of ideas for research questions. They are usually at an appropriate level of specificity and suggest research questions that focus on the following:
o a. Replicating a previous research project exactly or with slight variations.
o b. Exploring unexpected findings discovered in previous research.
o c. Following suggestions an author gives for future research at the end of an article.
o d. Extending an existing explanation or theory to a new topic or setting.
o e. Challenging the findings or attempting to refute a relationship.
o f. Specifying the intervening process and considering any linking relations.
2. Talk over ideas with others.
o a. Ask people who are knowledgeable about the topic for questions about it that they have thought of.
o b. Seek out those who hold opinions that differ from yours on the topic and discuss possible research questions with them.
3. Apply to a specific context.
o a. Focus the topic onto a specific historical period or time period.
o b. Narrow the topic to a specific society or geographic unit.
o c. Consider which subgroups or categories of people/ units are involved and whether there are differences among them.
4. Define the aim or desired outcome of the study.
o a. Will the research question be for an exploratory explanatory or descriptive study?
o b. Will the study involve applied or basic research?
example box 6.2 Examples of Bad and Good Research Questions
BAD RESEARCH QUESTIONS
Not Empirically Testable Nonscientific Questions
Should abortion be legal?
Is it right to have capital punishment?
General Topics Not Research Questions
Treatment of alcohol and drug abuse
Sexuality and aging
Set of Variables Not Questions
Capital punishment and racial discrimination
Urban decay and gangs
Too Vague Ambiguous
Do police affect delinquency?
What can be done to prevent child abuse?
Need to Be Still More Specific
Has the incidence of child abuse risen?
How does poverty affect children?
What problems do children who grow up in poverty experience that others do not? GOOD RESEARCH QUESTIONS
Exploratory Questions
Has the incidence of new forms of child abuse appeared in Wisconsin in the past 10 years?
Descriptive Questions
Is child abuse violent or sexual more common in families that have experienced a divorce than in intact never-divorced families?
Are the children raised in impoverished households more likely to have medical learning and social-emotional adjustment difficulties than children who are not living in poverty?
Explanatory Questions
Does the emotional instability created by experiencing a divorce increase the chances that divorced parents will physically abuse their children?
Is a lack of sufficent funds for preventive treatment a major cause of more serious medical problems among children raised in families in poverty?
We also want to specify the universe to which we generalize answers to a research question. All research questions and studies apply to some category of people organizations or other units. The universe is the set of all units that the research question covers or to which we can generalize. For example in Pagers (2007) study his units were individuals specifically young White and Black men. The universe to which we might generalize his findings includes all U.S. males in their twenties of these two racial categories.
Universe
The entire category or class of units that is covered or explained by a relationship or hypothesis.
As we refine a topic into a research question and design a study we also need to consider practical limitations. Designing the perfect research project is an interesting academic exercise but if we expect to carry out a study practical limitations must shape its design. Major limitations include time costs access to resources approval from authorities ethical concerns and expertise. If we have 10 hours a week for 5 weeks to conduct a research project but answering the research question will require 2 years we must narrow the question to fit the practical limitations.
Time is always a consideration. However it is very difficult to estimate the time required for a study. A specific research question the research techniques used the complexity of the study and the amount and types of data we plan to collect all affect the amount of time required. Experienced researchers are the best source for getting good estimates of time requirements.
Cost is another limitation and we cannot answer some research questions because of the great expense involved. For example our research question asks whether sports fans develop strong positive feelings toward team mascots if the team has a winning season but negative feelings if it has a losing season. To examine the question for all sports teams across a nation across a decade would require a great investment of time and money. The focus could be narrowed to one sport (football) to sports played in college and to student fans at just four colleges across three seasons. As with time experienced researchers can help provide estimates of the cost to conduct a study.
table 6.1 Quantitative Research versus Qualitative Research
quantitative research qualitative research
Researchers test hypotheses that are stated at the beginning. Researchers capture and discover meaning once they become immersed in the data.
Concepts are in the form of distinct variables. Concepts are in the form of themes motifs generalizations and taxonomies.
Measures are systematically created before data collection and are standardized. Measures are created in an ad hoc manner and are often specific to the individual setting or researcher.
Data are in the form of numbers from precise measurement. Data are in the form of words and images from documents observations and transcripts.
Theory is largely causal and is deductive. Theory can be causal or noncausal and is often inductive.
Procedures are standard and replication is frequent. Research procedures are particular and replication is very rare.
Analysis proceeds by using statistics tables or charts and discussing how what they show relates to hypotheses. Analysis proceeds by extracting themes or generalizations from evidence and organizing data to present a coherent consistent picture.
Access to resources is a common limitation. Resources include expertise special equipment and information. For example a research question about burglary rates and family income in many different nations is nearly impossible to answer. Data on burglary and income are not collected or available for many countries. Other questions require the approval of authorities (e.g. to see medical records) or involve violating basic ethical principles (e.g. lying to a person and endangering her or him). Our expertise or background as researchers is also a limitation. Answering some research questions involves the use of data collection techniques statistical methods knowledge of a foreign language or skills we may not have. Unless we acquire the necessary training or can pay for another persons services the research question may not be practical.
In sum qualitative and quantitative studies share a great deal but they differ on several design issues: logic research path mode of verification and way to arrive at a research question (seeTable 6.1). In addition the research approaches speak different languages and emphasize distinct study design features issues that we consider in the next section.
QUALITATIVE DESIGN ISSUES
The Language of Cases and Contexts
Most qualitative studies involve a language of cases and contexts employ bricolage (discussed later in this chapter) examine social processes and cases in their social context and study interpretations or meanings in specific socio-cultural settings. We examine social life from multiple points of view and explain how people construct identities. Only rarely do we use variables test hypotheses or create precise measures in the form of numbers.
Most qualitative studies build on the assumption that certain areas of social life are intrinsicallyqualitative. For this reason qualitative data are not imprecise or deficient but are very meaningful. Instead of trying to convert fluid active social life into variables or numbers we borrow ideas and viewpoints from the people we study and situate them in a fluid natural setting. Instead of variables we examine motifs themes distinctions and perspectives. Most often our approach is inductive and relies on a form of grounded theory (discussed in Chapter 3).
Qualitative data may appear to be soft intangible and elusive. This does not mean that we cannot capture them. We gather qualitative data by documenting real events recording what actual people say (with words gestures and tone) observing specific behaviors examining written documents and studying visual images. These are specific concrete aspects of the social world. As we closely scrutinize photos or videotapes of people or social events we are looking at hard physical evidence.10 The evidence is just as hard and physical as the numeric measures of attitudes social pressure intelligence and the like found in a quantitative study.
Grounded Theory
In qualitative research we may develop theory during the data collection process. This largely inductive method means that we are building theory from data or ground the theory in the data. Grounded theory adds flexibility and allows the data and theory to interact. This process also helps us remain open to the unexpected. We can change direction of study and even abandon the original research question in the middle of a project if we discover something new and exciting.11
We build theory by making comparisons. For example we observe an event (e.g. a police officer confronting a speeding motorist who has stopped). We may ponder questions and look for similarities and differences. When watching a police officer we ask: Does the police officer always radio in the cars license number before proceeding? After radioing the cars location does the officer ask the motorist to get out of the car or some times casually walk up to the car and talk to the seated driver? When we intersperse data collection and theorizing new theoretical questions may arise that suggest future observations. In this way we tailor new data to answer theoretical questions that arose only from thinking about previous data.
In grounded theory we build from specific observations to broader concepts that organize observational data and then continue to build principles or themes that connect the concepts. Compared to other ways of theorizing grounded theory tends to be less abstract and closer to concrete observations or specific events. Building inductively from the data to theory creates strong data-theory linkages. However this can be a weakness as well. It may make connecting concepts and principles across many diverse settings difficult and it may slow the development of concepts that build toward creating general abstract knowledge. To counteract this weakness we become familiar with the concepts and theories developed in other studies to apply shared concepts when appropriate and to note any similarities and differences. In this way we can establish cross-study interconnections and move toward generalized knowledge.
The Context Is Critical
In qualitative research we usually emphasize the social context because the meaning of a social action event or statement greatly depends on the context in which it appears. If we strip social context from an event social action or conversation it is easy to distort its meaning and alter its social significance.
Social context includes time context (when something occurs) spatial context (where something occurs) emotional context (the feelings regarding how something occurs) and socio-cultural context (the social situation and cultural milieu in which something occurs). For example a social activity (a card game sexual act or disagreement) occurs late at night on the street in a low-income area of a large city a setting for drug use fear and anger violent crime and prostitution within a cultural milieu of extreme racial-economic inequality. The same activity occurs midday in the backyard of a large house in an affluent suburban neighborhood in a social setting of relaxation and leisure surrounded by trust and emotional closeness and within a cultural milieu of established affluence and privilege. The context will significantly color the activitys meaning. With different contextual meanings the same activity or behavior may have different consequences.
In a quantitative study we rarely treat context as important. We often strip it away as being messy or just noise and instead concentrate on precise counts or numerical measures. Thus what a qualitative study might treat as essential may be seen as irrelevant noise in a quantitative study. For example if a quantitative study counts the number of votes across time or cultures a qualitative researcher might consider what voting means in the context. He or she may treat the same behavior (e.g. voting for a presidential candidate) differently depending on the social context in which it occurs (see Example Box 6.3 Example of Importance of Context for Meaning).
Context goes beyond social events behaviors and statements to include physical objects. One handgun could be an art object part of a recreational hobby a key element in committing a violent crime evidence of an irresponsible parent a suicide facilitator or a means of social peace and community protection each depending on the context. Without including the surrounding context we cannot assign meaning to an object.
example box 6.3 Example of the Importance of Context for Meaning
Voting in a national election has different meanings in different contexts:
1. A one-party dictatorship with unopposed candidates where people are required by law to vote. The names of nonvoters are recorded by the police. Nonvoters are suspected of being antigovernment subversives. They face fines and possible job loss for not voting.
2. A country in the midst of violent conflict between rebels and those in power. Voting is dangerous because the armed soldiers on either side may shoot voters they suspect of opposing their side. The outcome of the vote will give power to one or the other group and dramatically restructure the society. Anyone over the age of 16 can vote.
3. A context in which people choose between a dozen political parties of roughly equal power that represent very different values and policies. Each party has a sizable organization with its own newspapers social clubs and neighborhood organizers. Election days are national holidays when no one has to work. A person votes by showing up with an identification card at any of many local voting locations. Voting itself is by secret ballot and everyone over age 18 can vote.
4. A context in which voting is conducted in public by White males over age 21 who have regular jobs. Family friends and neighbors see how one another vote. Political parties do not offer distinct policies; instead they are tied to ethnic or religious groups and are part of a persons ethnic-religious identity. Ethnic and religious group identities are very strong. They affect where one lives where one works whom one marries and the like. Voting follows massive parades and week-long community events organized by ethnic and religious groups.
5. A context in which one political party is very powerful and is challenged by one or two very small weak alternatives. The one party has held power for the past 60 years through corruption bribery and intimidation. It has the support of leaders throughout society (in religious organizations educational institutions businesses unions and the mass media). The jobs of anyone working in any government job (e.g. every police officer post office clerk schoolteacher and garbage collector) depend on the political party staying in power.
6. A context in which the choice is between two parties with little difference between them. People select candidates primarily on the basis of television advertising. Candidates pay for advertising with donations by wealthy people or powerful organizations. Voting is a vague civic obligation that few people take seriously. Elections are held on a workday. In order to vote a person must meet many requirements and register to vote several weeks in advance. Recent immigrants and anyone arrested for a crime are prohibited from voting.
Bricolage
A bricoleur is someone who has learned to be adept in diverse areas can draw on a variety of sources and makes do with whatever is at hand.12 The bricolage technique involves working with ones hands and combining odds and ends in a practical skilled and inventive way to accomplish a task. A successful bricoleur possesses a deep knowledge of materials a set of esoteric skills and a capacity to combine or create flexibly. The typical bricoleur is often a highly inventive and skilled craftsperson repairperson or jack-of-all-trades.
Bricolage
Improvisation by drawing on diverse materials that are lying about and using them in creative ways to accomplish a pragmatic task.
A qualitative study draws on a variety of skills materials and approaches as needed. This usually happens when we are unable to anticipate the need for them. The process of mixing diverse source materials applying disparate approaches and assembling bits and pieces into a whole is analogous to the bricolage of a skilled craftsperson who is able to create or repair many things by using whatever is available at the time.
The Case and Process
We can divide all empirical social research into two groups: case study (with one or a few cases) orcross-case (comprising many cases).13 Most qualitative studies use a case-oriented approach [that] places cases not variables center stage (Ragin 1992a:5). Thus we examine many aspects of a few cases. The intensive in-depth study a handful of cases replaces the extensive surface-level study of numerous cases as is typical in quantitative research. Often a case-oriented analysis emphasizes contingencies in messy natural settings (i.e. the co-occurrence of many specific factors and events in one place and at one time). Rather than precise measures of a huge number of cases as is typical of quantitative research we acquire in-depth of knowledge and an astute insight into a small number of cases.
The study of cases tends to produce complex explanations or interpretations in the form of an unfolding plot or a narrative story about particular people or specific events. This makes the passage of time integral to the explanation. Often the emphasis becomes the sequence of events: what occurred first second third and so on. This focus on process helps to reveal how an issue evolves a conflict emerges or a social relationship develops.
Interpretation
To interpret means to assign significance or coherent meaning. In quantitative research meaning comes from using numbers (e.g. percentages or statistical coefficients) and we explain how the numerical data relate to the hypotheses. Qualitative studies rarely include tables with numbers. The only visual presentations of data may be maps photographs or diagrams showing how ideas are related. We instead weave the data into discussions of the ideas significance. The data are in the form of words including quotes or descriptions of particular events. Any numerical information is supplementary to the textual evidence.
Qualitative studies give data meaning translate them or make them understandable. We begin with the point of view of the people we study and then find out how they see the world and define situations. We learn what events behaviors and activities mean for them. To begin qualitative interpretation we first must learn the meanings of things for the people we are studying.14
People who create social activities and behavior have personal reasons or motives for what they do. This is first-order interpretation. As we discover and reconstruct this first-order interpretation it becomes a second-order interpretation because we come from the outside to discover what has occurred. In a second-order interpretation we elicit an underlying coherence or sense of meaning in the data. Meaning develops only in relation to a large set of other meanings not in a vacuum. In a second-order interpretation we place the human action being studied into a stream of behavior or events to which it is related: its context.
First-order interpretation
Interpretations from the point of view of the people being studied.
Second-order interpretation
Qualitative interpretations from the point of view of the researcher who conducted a study.
If we were to adopt a very strict interpretive approach we might stop at a second-order interpretation that is once we understand the significance of the action for the people we study. Most qualitative researchers go further. They want to generalize or link the second-order interpretation to a theory or general knowledge. They move to a broad level of interpretation orthird-order interpretation by which they assign general theoretical significance to the data.
Third-order interpretation
Qualitative interpretations made by the readers of a research report.
Because interpreting social meaning in context is often a major purpose and outcome of qualitative studies keep in mind that the three steps or orders of interpretation help provide a way to organize the research process.
QUANTITATIVE DESIGN ISSUES
The Language of Variables and Hypotheses
Variation and Variables.
Simply defined a variable is a concept that varies. In quantitative research we use a language of variables and relationships among variables.
Variable
A concept or its empirical measure that can take on multiple values.
In Chapter 3 we discussed two types of concepts: those that refer to a fixed phenomenon (e.g. the ideal type of bureaucracy) and those that vary in quantity intensity or amount (e.g. amount of education). Variables are this second type of concept and measures of the concepts.
A variable must have two or more values. Once we become aware of them we see variables everywhere. For example gender is a variable; it can take one of two values: male or female. Marital status is a variable; it can take the value of never married single married divorced or widowed. Type of crime committed is a variable; it can take values of robbery burglary theft murder and so forth. Family income is a variable; it can take values from zero to billions of dollars. A persons attitude toward abortion is a variable; as a womans basic right can range from strongly favoring legal abortion to strongly believing in the sanctity of fetal life.
A variables values or categories are its attributes. It is easy to confuse variables with attributes. The confusion arises because one variables attribute can itself be a separate variable in its own right with only a slight change in definition. This rests on a distinction between concepts that vary and the conditions within concepts that vary. For example male is not a variable; it describes a category of gender. Male is an attribute of the variable gender yet a related idea degree of masculinity is a variable. It describes the intensity or strength of attachment to a set of beliefs orientations and behaviors that are associated with the concept of masculine within a culture. Likewise married is not a variable; it is an attribute of the variable marital status. Related ideas such as number of years married or depth of commitment to a marriage are variables. In a third example robbery is not a variable; but an attribute of the variable type of crime. Number of robberies robbery rate amount taken during a robbery and type of robbery are all variables because they vary or take on a range of values.
Attributes
The categories or levels of a variable.
In quantitative research we redefine all concepts into the language of variables. As the examples of variables and attributes illustrate the redefinition often requires only a slight change in definition. As noted in Chapter 3 concepts are the building blocks of theory; they organize thinking about the social world. Clear concepts with careful definitions are essential in theory.
Types of Variables.
As we focus on causal relations among variables we usually begin with an effect and then search for its cause(s). We can classify variables depending on their location in a causal relationship or chain of causality. The cause variable or the force or condition that acts on something else is theindependent variable. The variable that is the effect result or outcome of another variable is thedependent variable. The independent variable is independent of prior causes that have acted on it whereas the dependent variable depends on the cause.
Independent variable
A type of variable that produces an effect or results on a dependent variable in a causal hypothesis.
Dependent variable
The effect or result variable that is caused by an independent variable in a causal hypothesis.
It is not always easy to determine whether a variable is independent or dependent. Two questions can help to identify the independent variable. First does it come before other variables in time? Independent variables must come before any other type. Second if two variables occur at the same time does one variable have an impact on another variable? Independent variables affect or have an impact on other variables. We often phrase research topics and questions in terms of the dependent variable because dependent variables are the phenomena we want to explain. For example an examination of the reasons for an increase in the crime rate in Dallas Texas would have the dependent variable as the crime rate in Dallas.
A simple causal relationship requires only an independent and a dependent variable. A third variable type the intervening variable appears in more complex causal relations. Coming between the independent and dependent variables this variable helps to show the link or mechanism between them. As noted in Chapter 3 advances in knowledge depend not only on documenting cause-and-effect relationships but also on specifying the mechanisms that account for the causal relation. In a sense the intervening variable acts as a dependent variable with respect to the independent variable and acts as an independent variable toward the dependent variable.
Intervening variable
A variable that comes logically or temporally after the independent variable and before the dependent variable and through which their causal relation operates.
For example French sociologist mile Durkheim developed a theory of suicide that specified a causal relationship between marital status and suicide rate. Durkheim found evidence that married people are less likely to commit suicide than single people. He believed that married people have more social integration (i.e. feelings of belonging to a group or family). He thought that a major cause of one type of suicide was that people lacked a sense of belonging to a group. Thus his theory can be restated as a three-variable relationship: marital status (independent variable) causes the degree of social integration (intervening variable) which affects suicide (dependent variable). Specifying the chain of causality makes the linkages in a theory clearer and helps a researcher test complex explanations.15
Simple theories have one dependent and one independent variable whereas complex ones can contain dozens of variables with multiple independent intervening and dependent variables. For example a theory of criminal behavior (dependent variable) identifies four independent variables: an individuals economic hardship opportunities to commit crime easily membership in a deviant subgroup that does not disapprove of crime and lack of punishment for criminal acts. A multicause explanation usually specifies which independent variable has the most significant causal effect.
A complex theoretical explanation has a string of multiple intervening variables. For example family disruption causes lower self-esteem among children which causes depression which causes poor grades in school which causes reduced prospects for a good job which causes a lower adult income. The chain of variables is family disruption (independent) childhood self-esteem (intervening) depression (intervening) grades in school (intervening) job prospects (intervening) adult income (dependent).
Two theories on the same topic can differ as to the number of independent variables. In addition theories might agree about the independent and dependent variables but differ on the intervening variable or causal mechanism. For example two theories say that family disruption causes lower adult income each for different reasons. One theory holds that disruption encourages children to join deviant peer groups which are not socialized to the norms of work and thrift. Another theory emphasizes the impact of the disruption on childhood depression and poor academic performance. In the second theory depression and limited school learning directly cause poor job performance.
In one study we usually test only one or a few parts of a causal chain. For example a research project examining six variables may take the six from a large complex theory with two dozen variables. Explicit links to a larger theory strengthen and clarify a research project.
Causal Theory and Hypotheses
The Hypothesis and Causality.
A causal hypothesis is a proposition to be tested or a tentative statement of a relationship between two variables. Hypotheses are guesses about how the social world works; they are stated in a value-neutral form. Kerlinger (1979:35) noted that
Hypotheses are much more important in scientific research than they would appear to be just by knowing what they are and how they are constructed. They have a deep and highly significant purpose of taking man out of himself. Hypotheses are powerful tools for the advancement of knowledge because although formulated by man they can be tested and shown to be correct or incorrect apart from mans values and beliefs.
Causal hypothesis
A statement of a causal explanation or proposition that has at least one independent and one dependent variable and has yet to be empirically tested.
A causal hypothesis has five characteristics (see Expansion Box 6.4 Five Characteristics of Causal Hypotheses). For example we can restate the hypothesis that attending religious services reduces the probability of divorce as a prediction: Couples who attend religious services frequently have a lower divorce rate than do couples who rarely attend religious services. We can test the prediction against the empirical evidence. We should logically connect the hypothesis to a research question and to a broader theory; after all we test hypotheses to answer the research question or to find empirical support for a theory. Statements that are logically or necessarily true or questions that are impossible to answer through empirical observation (e.g. What is the good life? Is there a God?) are not scientific hypotheses.
expansion box 6.4 Five Characteristics of Casual Hypotheses
1. They have at least two variables.
2. They express a causal or causeeffect relationship between the variables.
3. They can be expressed as a prediction or an expected future outcome.
4. They are logically linked to a research question and a theory.
5. They are falsifiable; that is they are capable of being tested against empirical evidence and shown to be true or false.
We can state causal hypotheses in several ways. Sometimes we use the word cause but it is not necessary. For example we can state a causal hypothesis between religious attendance and a reduced likelihood of divorce in ten different ways (see Example Box 6.4 Ways to State Causal Relations).
In scientific research we avoid using the term proved when talking about testing hypotheses. Journalism courts of law and advertisements use the word proof but a research scientist almost never uses it. A jury says that the evidence proves someone guilty or a television commercial will state Studies prove that our aspirin cures headaches the fastest. This is not the language of scientific research. In science we recognize that knowledge is tentative and that creating knowledge is an ongoing process that avoids premature closure. The word proof implies finality absolute certainty or something that does not need further investigation. It is too strong a term for the cautious world of science. We might say that the evidence supports or confirms but does not prove the hypothesis. Even after hundreds of studies show the same results such as the link between cigarette smoking and lung cancer scientists do not say that we have absolute proof. Instead we can say that overwhelming evidence or all studies to date support or are consistent with the hypothesis. Scientists never want to close off the possibility of discovering new evidence that might contradict past findings. They do not want to cut off future inquiry or stop exploring intervening mechanisms. History contains many examples of relationships that people once thought to be proved but were later found to be in error. We can use proof when referring to logical or mathematical relations as in a mathematical proof but not for empirical research.
example box 6.4 Ways to State Casual Relations
Religious attendance causes reduced divorce. Religious attendance leads to reduced divorce.
Religious attendance is related to reduced divorce.
Religious attendance influences the reduction of divorce.
Religious attendance is associated with reduced divorce.
Religious attendance produces reduced divorce.
Religious attendance results in reduced divorce.
If people attend religious services then the likelihood of divorce will be reduced.
The higher religious attendance the lower the likelihood of divorce.
Religious attendance reduces the likelihood of divorce.
Testing and Refining a Hypothesis.
Knowledge rarely advances on the basis of one test of a single hypothesis. In fact researchers can get a distorted picture of the research process by focusing on a single study that tests one hypothesis. Knowledge develops over time as many researchers across the scientific community test many hypotheses. It slowly grows from shifting and winnowing through many hypotheses. Each hypothesis represents an explanation of a dependent variable. If the evidence fails to support some hypotheses they are gradually eliminated from consideration. Those that receive support remain in contention. Theorists and researchers constantly create new hypotheses to challenge those that have received support (see Figure 6.3 on page 182). From Figure 6.3 we see that in 2010 three hypotheses are in contention but from 1970 to 2010 eleven hypotheses were considered and over time eight of them were rejected in one or more tests.
Scientists are a skeptical group. Supporting a hypothesis in one study is not sufficient for them to accept it. The principle of replication says that a hypothesis needs several tests with consistent and repeated support before it can gain broad acceptance. Another way to strengthen confidence in a hypothesis is to test related causal linkages in the theory from which it comes.
As scientists we accept the strongest contender with the greatest empirical support as the best explanation at the time. The more alternatives we test a hypothesis against the more confidence we have in it. Some tests are called crucial experiments or crucial studies. This is a type of study whereby
two or more alternative explanations for some phenomenon are available each being compatible with the empirically given data; the crucial experiment is designed to yield results that can be accounted for by only one of the alternatives which is thereby shown to be the correct explanation. (Kaplan 1964:151152)
Crucial experiment
A direct comparison and evaluation of competing explanations of the same phenomenon designed to show that one is superior to the other.
Thus the infrequent crucial experiment is an important test of theory. Hypotheses from two different theories confront each other in crucial experiments and one is knocked out of the competition. It is rare but significant when it occurs.
Types of Hypotheses.
Hypotheses are links in a theoretical causal chain and are used to test the direction and strength of a relationship between variables. When a hypothesis defeats its competitors it supports the researchers explanation. A curious aspect of hypothesis testing is that researchers treat evidence that supports a hypothesis differently from evidence that opposes it: They give negative evidence more importance. The idea that negative evidence is critical when evaluating a hypothesis comes from the logic of disconfirming hypotheses.16 It is associated with Karl Poppers idea of falsification (see Chapter 4 under positivism) and with the use of null hypotheses (see later in this section).
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