hypothesis in sociology notes

Hypothesis: Functions, Problems, Types, Characteristics, Examples

Basic Elements of the Scientific Method: Hypotheses

The Function of the Hypotheses

A hypothesis states what one is looking for in an experiment. When facts are assembled, ordered, and seen in a relationship, they build up to become a theory. This theory needs to be deduced for further confirmation of the facts, this formulation of the deductions constitutes of a hypothesis. As a theory states a logical relationship between facts and from this, the propositions which are deduced should be true. Hence, these deduced prepositions are called hypotheses.

Problems in Formulating the Hypothesis

As difficult as the process may be, it is very essential to understand the need of a hypothesis. The research would be much unfocused and a random empirical wandering without it. The hypothesis provides a necessary link between the theory and investigation which often leads to the discovery of additions to knowledge.

There are three major difficulties in the formulation of a hypothesis, they are as follows:

• Absence of a clear theoretical framework
• Lack of ability to utilize that theoretical framework logically
• Failure to be acquainted with available research techniques so as to phrase the hypothesis properly.

Sometimes the deduction of a hypothesis may be difficult as there would be many variables and the necessity to take them all into consideration becomes a challenge. For instance, observing two cases:

• Principle: A socially recognized relationship with built-in strains also governed by the institutional controls has to ensure conformity of the participants with implicit or explicit norms.

Deduction: This situation holds much more sense to the people who are in professions such as psychotherapy, psychiatry and law to some extent. They possess a very intimate relationship with their clients, thus are more susceptible to issues regarding emotional strains in the client-practitioner relationship and more implicit and explicit controls over both participants in comparison to other professions.

The above-mentioned case has variable hypotheses, so the need is to break them down into sub hypotheses, they are as follows:

• Specification of the degree of difference
• Specification of profession and problem
• Specification of kinds of controls.

2. Principle: Extensive but relatively systematized data show the correlation between members of the upper occupational class and less unhappiness and worry. Also, they are subjected to more formal controls than members of the lower strata.

Deduction: There can numerous ways to approach this principle, one could go with the comparison applying to martial relationships of the members and further argue that such differential pressures could be observed through divorce rates. This hypothesis would show inverse correlations between class position and divorce rates. There would be a very strong need to define the terms carefully to show the deduction from the principle problem.

The reference of these examples showcases a major issue in the hypothesis formulations procedures. One needs to keep the lines set for the deductions and one should be focusing on having a hypothesis at the beginning of the experiment, that hypothesis may be subject to change in the later stages and it is referred to as a „working hypothesis. Hence, the devising and utilization of a hypothesis is essential for the success of the experiment.

Types of Hypothesis

There are many ways to classify hypotheses, but it seems adequate to distinguish to separate them on the basis of their level of abstraction. They can be divided into three broad levels which will be increasing in abstractness.

• The existence of empirical uniformities : These hypotheses are made from problems which usually have a very high percentage of representing scientific examination of common–sense proportions. These studies may show a variety of things such as the distribution of business establishments in a city, behavior patterns of specific groups, etc. and they tend to show no irregularities in their data collection or review. There have been arguments which say that these aren’t hypothesis as they represent what everyone knows. This can be counter argued on the basis of two things that, “what everyone knows” isn’t always in coherence with the framework of science and it may also be incorrect. Hence, testing these hypotheses is necessary too.
• Complex ideal types: These hypotheses aim at testing the existence of logically derived relationships between empirical uniformities. This can be understood with an example, to observe ecology one should take in many factors and see the relationship between and how they affect the greater issue. A theory by Ernest W. Burgess gave out the statement that concentric growth circles are the one which characterize the city. Hence, all issues such as land values, industrial growth, ethnic groups, etc. are needed to be analyzed for forming a correct and reasonable hypothesis.
• Relations of analytic variables: These hypotheses are a bit more complex as they focus on they lead to the formulation of a relationship between the changes in one property with respect to another. For instance, taking the example of human fertility in diverse regions, religions, wealth gap, etc. may not always affect the end result but it doesn’t mean that the variables need not be accounted for. This level of hypothesizing is one of the most effective and sophisticated and thus is only limited by theory itself.

Science and Hypothesis

“The general culture in which a science develops furnishes many of its basic hypotheses” holds true as science has developed more in the West and is no accident that it is a function of culture itself. This is quite evident with the culture of the West as they read for morals, science and happiness. After the examination of a bunch of variables, it is quite easy to say that the cultural emphasis upon happiness has been productive of an almost limitless range.

The hypotheses originate from science; a key example in the form of “socialization” may be taken. The socialization process in learning science involves a feedback mechanism between the scientist and the student. The student learns from the scientist and then tests for results with his own experience, and the scientist in turn has to do the same with his colleagues.

Analogies are a source of useful hypotheses but not without its dangers as all variables may not be accounted for it as no civilization has a perfect system.

Hypotheses are also the consequence of personal, idiosyncratic experience as the manner in which the individual reacts to the hypotheses is also important and should be accounted for in the experiment.

The Characteristics for Usable Hypotheses

The criteria for judging a hypothesis as mentioned below:

• Complete Clarity : A good hypothesis should have two main elements, the concepts should be clearly defined and they should be definitions which are communicable and accepted by a larger section of the public. A lot of sources may be used and fellow associates may be used to help with the cause.
• Empirical Referents : A great hypothesis should have scientific concepts with the ultimate empirical referent. It can‟t be based on moral judgment though it can explore them but the goal should be separated from moral preachment and the acceptance of values. A good start could be analyzing the concepts which express attitudes rather than describing or referring to empirical phenomena.
• Specific Goal : The goal and procedure of the hypothesis should be tangible as grand experiments are harder to carry out. All operations and predictions should be mapped and in turn the possibility of testing the hypothesis increases. This not only enables the conceptual clarity but also the description of any indexes used. These indexes are used as variables for testing hypotheses on a larger scale. A general prediction isn’t as reliable as a specific prediction as the specific prediction provides a better result.
• Relation to Available Techniques : The technique with which a hypothesis is tested is of the utmost importance and so thorough research should be carried out before the experiment in order to find the best possible way to go about it. The example of Karl Marx may be given regarding his renowned theories; he formulated his hypothesis by observing individuals and thus proving his hypothesis. So, finding the right technique may be the key to a successful test.
• Relation to a Body of Theory: Theories on social relations can never be developed in isolation but they are a further extension of already developed or developing theories. For instance, if the “intelligence quotient” of a member of the society is to be measured, certain variables such as caste, ethnicity, nationality, etc. are chosen thus deductions are made from time to time to eventually find out what is the factor that influences intelligence.

The Conclusion

The formulation of a hypothesis is probably the most necessary step in good research practice and it is very essential to get the thought process started. It helps the researcher to have a specific goal in mind and deduce the end result of an experiment with ease and efficiency. History is evident that asking the right questions always works out fine.

Also Read: Research Methods – Basics

Goode, W. E. and P. K. Hatt. 1952. Methods in Social Research.New York: McGraw Hill. Chapters 5 and 6. Pp. 41-73

Kartik is studying BA in International Relations at Amity and Dropped out of engineering from NIT Hamirpur and he lived in over 5 different countries.

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Developing a Research Question

18 Hypotheses

When researchers do not have predictions about what they will find, they conduct research to answer a question or questions, with an open-minded desire to know about a topic, or to help develop hypotheses for later testing. In other situations, the purpose of research is to test a specific hypothesis or hypotheses.  A hypothesis is a statement, sometimes but not always causal, describing a researcher’s expectations regarding anticipated finding. Often hypotheses are written to describe the expected relationship between two variables (though this is not a requirement). To develop a hypothesis, one needs to understand the differences between independent and dependent variables and between units of observation and units of analysis. Hypotheses are typically drawn from theories and usually describe how an independent variable is expected to affect some dependent variable or variables. Researchers following a deductive approach to their research will hypothesize about what they expect to find based on the theory or theories that frame their study. If the theory accurately reflects the phenomenon it is designed to explain, then the researcher’s hypotheses about what would be observed in the real world should bear out.

Sometimes researchers will hypothesize that a relationship will take a specific direction. As a result, an increase or decrease in one area might be said to cause an increase or decrease in another. For example, you might choose to study the relationship between age and legalization of marijuana. Perhaps you have done some reading in your spare time, or in another course you have taken.  Based on the theories you have read, you hypothesize that “age is negatively related to support for marijuana legalization.” What have you just hypothesized? You have hypothesized that as people get older, the likelihood of their support for marijuana legalization decreases. Thus, as age moves in one direction (up), support for marijuana legalization moves in another direction (down). If writing hypotheses feels tricky, it is sometimes helpful to draw them out. and depict each of the two hypotheses we have just discussed.

Note that you will almost never hear researchers say that they have proven their hypotheses. A statement that bold implies that a relationship has been shown to exist with absolute certainty and that there is no chance that there are conditions under which the hypothesis would not bear out. Instead, researchers tend to say that their hypotheses have been supported (or not) . This more cautious way of discussing findings allows for the possibility that new evidence or new ways of examining a relationship will be discovered. Researchers may also discuss a null hypothesis, one that predicts no relationship between the variables being studied. If a researcher rejects the null hypothesis, he or she is saying that the variables in question are somehow related to one another.

Quantitative and qualitative researchers tend to take different approaches when it comes to hypotheses. In quantitative research, the goal often is to empirically test hypotheses generated from theory. With a qualitative approach, on the other hand, a researcher may begin with some vague expectations about what he or she will find, but the aim is not to test one’s expectations against some empirical observations. Instead, theory development or construction is the goal. Qualitative researchers may develop theories from which hypotheses can be drawn and quantitative researchers may then test those hypotheses. Both types of research are crucial to understanding our social world, and both play an important role in the matter of hypothesis development and testing.  In the following section, we will look at qualitative and quantitative approaches to research, as well as mixed methods.

Text Attributions

• This chapter has been adapted from Chapter 5.2 in Principles of Sociological Inquiry , which was adapted by the Saylor Academy without attribution to the original authors or publisher, as requested by the licensor. © Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License .

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Chapter 2. Sociological Research

Learning objectives.

2.1. Approaches to Sociological Research

• Define and describe the scientific method
• Explain how the scientific method is used in sociological research
• Understand the difference between positivist and interpretive approaches to the scientific method in sociology
• Define what reliability and validity mean in a research study

2.2. Research Methods

• Differentiate between four kinds of research methods: surveys, experiments, field research, and secondary data and textual analysis
• Understand why different topics are better suited to different research approaches

2.3. Ethical Concerns

• Understand why ethical standards exist
• Demonstrate awareness of the Canadian Sociological Association’s Code of Ethics
• Define value neutrality
• Outline some of the issues of value neutrality in sociology

Introduction to Sociological Research

In the university cafeteria, you set your lunch tray down at a table, grab a chair, join a group of your classmates, and hear the start of two discussions. One person says, “It’s weird how Justin Bieber has 48 million followers on Twitter.” Another says, “Disney World is packed year round.” Those two seemingly benign statements are claims, or opinions, based on everyday observation of human behaviour. Perhaps the speakers had firsthand experience, talked to experts, conducted online research, or saw news segments on TV. In response, two conversations erupt. “I don’t see why anyone would want to go to Disney World and stand in those long lines.” “Are you kidding?! Going to Disney World is one of my favourite childhood memories.” “It’s the opposite for me with Justin Bieber. Seeing people camp out outside his hotel just to get a glimpse of him; it doesn’t make sense.” “Well, you’re not a teenage girl.” “Going to a theme park is way different than trying to see a teenage heart throb.” “But both are things people do for the same reason: they’re looking for a good time.” “If you call getting crushed by a crowd of strangers fun.”

As your classmates at the lunch table discuss what they know or believe, the two topics converge. The conversation becomes a debate. Someone compares Beliebers to Beatles fans. Someone else compares Disney World to a cruise. Students take sides, agreeing or disagreeing, as the conversation veers to topics such as crowd control, mob mentality, political protests, and group dynamics. If you contributed your expanding knowledge of sociological research to this conversation, you might make statements like these: “Justin Bieber’s fans long for an escape from the boredom of real teenage life. Beliebers join together claiming they want romance, except what they really want is a safe place to explore the confusion of teenage sexual feelings.” And this: “Mickey Mouse is a larger-than-life cartoon celebrity. Disney World is a place where families go to see what it would be like to live inside a cartoon.” You finish lunch, clear away your tray, and hurry to your next class. But you are thinking of Justin Bieber and Disney World. You have a new perspective on human behaviour and a list of questions that you want answered. That is the purpose of sociological research—to investigate and provide insights into how human societies function.

Although claims and opinions are part of sociology, sociologists use empirical evidence (that is, evidence corroborated by direct experience and/or observation) combined with the scientific method or an interpretive framework to deliver sound sociological research. They also rely on a theoretical foundation that provides an interpretive perspective through which they can make sense of scientific results. A truly scientific sociological study of the social situations up for discussion in the cafeteria would involve these prescribed steps: defining a specific question, gathering information and resources through observation, forming a hypothesis, testing the hypothesis in a reproducible manner, analyzing and drawing conclusions from the data, publishing the results, and anticipating further development when future researchers respond to and retest findings.

An appropriate starting point in this case might be the question “What do fans of Justin Bieber seek that drives them to follow his Twitter comments so faithfully?” As you begin to think like a sociologist, you may notice that you have tapped into your observation skills. You might assume that your observations and insights are valuable and accurate. But the results of casual observation are limited by the fact that there is no standardization—who is to say one person’s observation of an event is any more accurate than another’s? To mediate these concerns, sociologists rely on systematic research processes.

When sociologists apply the sociological perspective and begin to ask questions, no topic is off limits. Every aspect of human behaviour is a source of possible investigation. Sociologists question the world that humans have created and live in. They notice patterns of behaviour as people move through that world. Using sociological methods and systematic research within the framework of the scientific method and a scholarly interpretive perspective, sociologists have discovered workplace patterns that have transformed industries, family patterns that have enlightened parents, and education patterns that have aided structural changes in classrooms. The students at that university cafeteria discussion put forth a few loosely stated opinions.

If the human behaviours around those claims were tested systematically, a student could write a report and offer the findings to fellow sociologists and the world in general. The new perspective could help people understand themselves and their neighbours and help people make better decisions about their lives. It might seem strange to use scientific practices to study social trends, but, as we shall see, it’s extremely helpful to rely on systematic approaches that research methods provide. Sociologists often begin the research process by asking a question about how or why things happen in this world. It might be a unique question about a new trend or an old question about a common aspect of life. Once a question is formed, a sociologist proceeds through an in-depth process to answer it. In deciding how to design that process, the researcher may adopt a positivist approach or an interpretive approach. The following sections describe these approaches to knowledge.

The Scientific Method

Sociologists make use of tried-and-true methods of research, such as experiments, surveys, field research, and textual analysis. But humans and their social interactions are so diverse that they can seem impossible to chart or explain. It might seem that science is about discoveries and chemical reactions or about proving ideas right or wrong rather than about exploring the nuances of human behaviour. However, this is exactly why scientific models work for studying human behaviour. A scientific process of research establishes parameters that help make sure results are objective and accurate. Scientific methods provide limitations and boundaries that focus a study and organize its results. This is the case for both positivist or quantitative methodologies and interpretive or qualitative methodologies. The scientific method involves developing and testing theories about the world based on empirical evidence. It is defined by its commitment to systematic observation of the empirical world and strives to be objective, critical, skeptical, and logical. It involves a series of prescribed steps that have been established over centuries of scholarship.

But just because sociological studies use scientific methods does not make the results less human. Sociological topics are not reduced to right or wrong facts. In this field, results of studies tend to provide people with access to knowledge they did not have before—knowledge of other cultures, knowledge of rituals and beliefs, knowledge of trends and attitudes. No matter what research approach is used, researchers want to maximize the study’s reliability (how likely research results are to be replicated if the study is reproduced). Reliability increases the likelihood that what is true of one person will be true of all people in a group. Researchers also strive for validity (how well the study measures what it was designed to measure).

Returning to the Disney World topic, reliability of a study would reflect how well the resulting experience represents the average experience of theme park-goers. Validity would ensure that the study’s design accurately examined what it was designed to study, so an exploration of adults’ interactions with costumed mascots should address that issue and not veer into other age groups’ interactions with them or into adult interactions with staff or other guests.

In general, sociologists tackle questions about the role of social characteristics in outcomes. For example, how do different communities fare in terms of psychological well-being, community cohesiveness, range of vocation, wealth, crime rates, and so on? Are communities functioning smoothly? Sociologists look between the cracks to discover obstacles to meeting basic human needs. They might study environmental influences and patterns of behaviour that lead to crime, substance abuse, divorce, poverty, unplanned pregnancies, or illness. And, because sociological studies are not all focused on problematic behaviours or challenging situations, researchers might study vacation trends, healthy eating habits, neighbourhood organizations, higher education patterns, games, parks, and exercise habits.

Sociologists can use the scientific method not only to collect but to interpret and analyze the data. They deliberately apply scientific logic and objectivity. They are interested in but not attached to the results. Their research work is independent of their own political or social beliefs. This does not mean researchers are not critical. Nor does it mean they do not have their own personalities, complete with preferences and opinions. But sociologists deliberately use the scientific method to maintain as much objectivity, focus, and consistency as possible in a particular study. With its systematic approach, the scientific method has proven useful in shaping sociological studies. The scientific method provides a systematic, organized series of steps that help ensure objectivity and consistency in exploring a social problem. They provide the means for accuracy, reliability, and validity. In the end, the scientific method provides a shared basis for discussion and analysis (Merton 1963). Typically, the scientific method starts with these steps—1) ask a question, 2) research existing sources, 3) formulate a hypothesis—described below.

Ask a Question

The first step of the scientific method is to ask a question, describe a problem, and identify the specific area of interest. The topic should be narrow enough to study within a geography and timeframe. “Are societies capable of sustained happiness?” would be too vague. The question should also be broad enough to have universal merit. “What do personal hygiene habits reveal about the values of students at XYZ High School?” would be too narrow. That said, happiness and hygiene are worthy topics to study.

Sociologists do not rule out any topic, but would strive to frame these questions in better research terms. That is why sociologists are careful to define their terms. In a hygiene study, for instance, hygiene could be defined as “personal habits to maintain physical appearance (as opposed to health),” and a researcher might ask, “How do differing personal hygiene habits reflect the cultural value placed on appearance?” When forming these basic research questions, sociologists develop an operational definition ; that is, they define the concept in terms of the physical or concrete steps it takes to objectively measure it. The concept is translated into an observable variable , a measure that has different values. The operational definition identifies an observable condition of the concept.

By operationalizing a variable of the concept, all researchers can collect data in a systematic or replicable manner. The operational definition must be valid in the sense that it is an appropriate and meaningful measure of the concept being studied. It must also be reliable, meaning that results will be close to uniform when tested on more than one person. For example, “good drivers” might be defined in many ways: those who use their turn signals, those who don’t speed, or those who courteously allow others to merge. But these driving behaviours could be interpreted differently by different researchers and could be difficult to measure. Alternatively, “a driver who has never received a traffic violation” is a specific description that will lead researchers to obtain the same information, so it is an effective operational definition.

Research Existing Sources

The next step researchers undertake is to conduct background research through a literature review , which is a review of any existing similar or related studies. A visit to the library and a thorough online search will uncover existing research about the topic of study. This step helps researchers gain a broad understanding of work previously conducted on the topic at hand and enables them to position their own research to build on prior knowledge. It allows them to sharpen the focus of their research question and avoid duplicating previous research. Researchers—including student researchers—are responsible for correctly citing existing sources they use in a study or that inform their work. While it is fine to build on previously published material (as long as it enhances a unique viewpoint), it must be referenced properly and never plagiarized. To study hygiene and its value in a particular society, a researcher might sort through existing research and unearth studies about childrearing, vanity, obsessive-compulsive behaviours, and cultural attitudes toward beauty. It’s important to sift through this information and determine what is relevant. Using existing sources educates a researcher and helps refine and improve a study’s design.

Formulate a Hypothesis

A hypothesis is an assumption about how two or more variables are related; it makes a conjectural statement about the relationship between those variables. It is an “educated guess” because it is not random but based on theory, observations, patterns of experience, or the existing literature. The hypothesis formulates this guess in the form of a testable proposition. However, how the hypothesis is handled differs between the positivist and interpretive approaches. Positivist methodologies are often referred to as hypothetico-deductive methodologies . A hypothesis is derived from a theoretical proposition. On the basis of the hypothesis a prediction or generalization is logically deduced. In positivist sociology, the hypothesis predicts how one form of human behaviour influences another.

Successful prediction will determine the adequacy of the hypothesis and thereby test the theoretical proposition. Typically positivist approaches operationalize variables as quantitative data ; that is, by translating a social phenomenon like “health” into a quantifiable or numerically measurable variable like “number of visits to the hospital.” This permits sociologists to formulate their predictions using mathematical language like regression formulas, to present research findings in graphs and tables, and to perform mathematical or statistical techniques to demonstrate the validity of relationships.

Variables are examined to see if there is a correlation between them. When a change in one variable coincides with a change in another variable there is a correlation. This does not necessarily indicate that changes in one variable causes a change in another variable, however, just that they are associated. A key distinction here is between independent and dependent variables. In research, independent variables are the cause of the change. The dependent variable is the effect , or thing that is changed. For example, in a basic study, the researcher would establish one form of human behaviour as the independent variable and observe the influence it has on a dependent variable. How does gender (the independent variable) affect rate of income (the dependent variable)? How does one’s religion (the independent variable) affect family size (the dependent variable)? How is social class (the dependent variable) affected by level of education (the independent variable)? For it to become possible to speak about causation, three criteria must be satisfied:

• There must be a relationship or correlation between the independent and dependent variables.
• The independent variable must be prior to the dependent variable.
• There must be no other intervening variable responsible for the causal relationship.

 Table 2.1. Examples of Dependent and Independent Variables Typically, the independent variable causes the dependent variable to change in some way.

At this point, a researcher’s operational definitions help measure the variables. In a study asking how tutoring improves grades, for instance, one researcher might define “good” grades as a C or better, while another uses a B+ as a starting point for “good.” Another operational definition might describe “tutoring” as “one-on-one assistance by an expert in the field, hired by an educational institution.” Those definitions set limits and establish cut-off points, ensuring consistency and replicability in a study. As the chart shows, an independent variable is the one that causes a dependent variable to change. For example, a researcher might hypothesize that teaching children proper hygiene (the independent variable) will boost their sense of self-esteem (the dependent variable). Or rephrased, a child’s sense of self-esteem depends, in part, on the quality and availability of hygienic resources.

Of course, this hypothesis can also work the other way around. Perhaps a sociologist believes that increasing a child’s sense of self-esteem (the independent variable) will automatically increase or improve habits of hygiene (now the dependent variable). Identifying the independent and dependent variables is very important. As the hygiene example shows, simply identifying two topics, or variables, is not enough: Their prospective relationship must be part of the hypothesis. Just because a sociologist forms an educated prediction of a study’s outcome doesn’t mean data contradicting the hypothesis are not welcome. Sociologists analyze general patterns in response to a study, but they are equally interested in exceptions to patterns.

In a study of education, a researcher might predict that high school dropouts have a hard time finding a rewarding career. While it has become at least a cultural assumption that the higher the education, the higher the salary and degree of career happiness, there are certainly exceptions. People with little education have had stunning careers, and people with advanced degrees have had trouble finding work. A sociologist prepares a hypothesis knowing that results will vary.

While many sociologists rely on the positivist hypothetico-deductive method in their research, others operate from an interpretive approach . While systematic, this approach does not follow the hypothesis-testing model that seeks to make generalizable predictions from quantitative variables. Instead, an interpretive framework seeks to understand social worlds from the point of view of participants, leading to in-depth knowledge. It focuses on qualitative data, or the meanings that guide people’s behaviour. Rather than relying on quantitative instruments like questionnaires or experiments, which can be artificial, the interpretive approach attempts to find ways to get closer to the informants’ lived experience and perceptions. Interpretive research is generally more descriptive or narrative in its findings. It can begin from a deductive approach, by deriving a hypothesis from theory and then seeking to confirm it through methodologies like in-depth interviews.

However, it is ideally suited to an inductive approach in which the hypothesis emerges only after a substantial period of direct observation or interaction with subjects. This type of approach is exploratory in that the researcher also learns as he or she proceeds, sometimes adjusting the research methods or processes midway to respond to new insights and findings as they evolve. Once the preliminary work is done, it’s time for the next research steps: designing and conducting a study, and drawing conclusions. These research methods are discussed below.

Sociologists examine the world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study—perhaps a positivist, quantitative method for conducting research and obtaining data, or perhaps an ethnographic study utilizing an interpretive framework. Planning the research design is a key step in any sociological study. When entering a particular social environment, a researcher must be careful. There are times to remain anonymous and times to be overt. There are times to conduct interviews and times to simply observe. Some participants need to be thoroughly informed; others should not know they are being observed. A researcher would not stroll into a crime-ridden neighbourhood at midnight, calling out, “Any gang members around?” And if a researcher walked into a coffee shop and told the employees they would be observed as part of a study on work efficiency, the self-conscious, intimidated baristas might not behave naturally.

In the 1920s, leaders of a Chicago factory called Hawthorne Works commissioned a study to determine whether or not changing certain aspects of working conditions could increase or decrease worker productivity. Sociologists were surprised when the productivity of a test group increased when the lighting of their workspace was improved. They were even more surprised when productivity improved when the lighting of the workspace was dimmed. In fact almost every change of independent variable—lighting, breaks, work hours—resulted in an improvement of productivity. But when the study was over, productivity dropped again.

Why did this happen? In 1953, Henry A. Landsberger analyzed the study results to answer this question. He realized that employees’ productivity increased because sociologists were paying attention to them. The sociologists’ presence influenced the study results. Worker behaviours were altered not by the lighting but by the study itself. From this, sociologists learned the importance of carefully planning their roles as part of their research design (Franke and Kaul 1978). Landsberger called the workers’ response the Hawthorne effect —people changing their behaviour because they know they are being watched as part of a study.

The Hawthorne effect is unavoidable in some research. In many cases, sociologists have to make the purpose of the study known for ethical reasons. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985). Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviours, early education, or the Ku Klux Klan. Researchers cannot just stroll into prisons, kindergarten classrooms, or Ku Klux Klan meetings and unobtrusively observe behaviours. In situations like these, other methods are needed. All studies shape the research design, while research design simultaneously shapes the study. Researchers choose methods that best suit their study topic and that fit with their overall goal for the research.

In planning a study’s design, sociologists generally choose from four widely used methods of social investigation: survey, experiment, field research, and textual or secondary data analysis (or use of existing sources). Every research method comes with plusses and minuses, and the topic of study strongly influences which method or methods are put to use.

As a research method, a survey collects data from subjects who respond to a series of questions about behaviours and opinions, often in the form of a questionnaire. The survey is one of the most widely used positivist research methods. The standard survey format allows individuals a level of anonymity in which they can express personal ideas.

At some point or another, everyone responds to some type of survey. The Statistics Canada census is an excellent example of a large-scale survey intended to gather sociological data. Customers also fill out questionnaires at stores or promotional events, responding to questions such as “How did you hear about the event?” and “Were the staff helpful?” You’ve probably picked up the phone and heard a caller ask you to participate in a political poll or similar type of survey: “Do you eat hot dogs? If yes, how many per month?” Not all surveys would be considered sociological research. Marketing polls help companies refine marketing goals and strategies; they are generally not conducted as part of a scientific study, meaning they are not designed to test a hypothesis or to contribute knowledge to the field of sociology. The results are not published in a refereed scholarly journal, where design, methodology, results, and analyses are vetted.

Often, polls on TV do not reflect a general population, but are merely answers from a specific show’s audience. Polls conducted by programs such as American Idol or Canadian Idol represent the opinions of fans but are not particularly scientific. A good contrast to these are the BBM Ratings, which determine the popularity of radio and television programming in Canada through scientific market research. Sociologists conduct surveys under controlled conditions for specific purposes. Surveys gather different types of information from people. While surveys are not great at capturing the ways people really behave in social situations, they are a great method for discovering how people feel and think—or at least how they say they feel and think. Surveys can track attitudes and opinions, political preferences, reported individual behaviours (such as sleeping, driving, or texting habits), or factual information such as employment status, income, and education levels. A survey targets a specific population , people who are the focus of a study, such as university athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes.

Most researchers choose to survey a small sector of the population, or a sample : that is, a manageable number of subjects who represent a larger population. The success of a study depends on how well a population is represented by the sample. In a random sample , every person in a population has the same chance of being chosen for the study. According to the laws of probability, random samples represent the population as a whole. For instance, an Ipsos Reid poll, if conducted as a nationwide random sampling, should be able to provide an accurate estimate of public opinion whether it contacts 2,000 or 10,000 people. However the validity of surveys can be threatened when part of the population is inadvertently excluded from the sample (e.g., telephone surveys that rely on land lines exclude people that use only cell phones) or when there is a low response rate. After selecting subjects, the researcher develops a specific plan to ask questions and record responses.

It is important to inform subjects of the nature and purpose of the study upfront. If they agree to participate, researchers thank subjects and offer them a chance to see the results of the study if they are interested. The researcher presents the subjects with an instrument (a means of gathering the information). A common instrument is a structured questionnaire, in which subjects answer a series of set questions. For some topics, the researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question.

This kind of quantitative data —research collected in numerical form that can be counted—is easy to tabulate. Just count up the number of “yes” and “no” answers or tabulate the scales of “strongly agree,” “agree,” disagree,” etc. responses and chart them into percentages. This is also their chief drawback however: their artificiality. In real life, there are rarely any unambiguously yes-or-no answers. Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” “agree,” “strongly agree,” or an option next to a checkbox. In those cases, the answers are subjective, varying from person to person. How do you plan to use your university education? Why do you follow Justin Bieber around the country and attend every concert? Those types of questions require short essay responses, and participants willing to take the time to write those answers will convey personal information about religious beliefs, political views, and morals.

Some topics that reflect internal thought are impossible to observe directly and are difficult to discuss honestly in a public forum. People are more likely to share honest answers if they can respond to questions anonymously. This type of information is qualitative data —results that are subjective and often based on what is seen in a natural setting. Qualitative information is harder to organize and tabulate. The researcher will end up with a wide range of responses, some of which may be surprising. The benefit of written opinions, though, is the wealth of material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and is a way of conducting surveys on a topic. Interviews are similar to the short answer questions on surveys in that the researcher asks subjects a series of questions. However, participants are free to respond as they wish, without being limited by predetermined choices. In the back-and-forth conversation of an interview, a researcher can ask for clarification, spend more time on a subtopic, or ask additional questions. In an interview, a subject will ideally feel free to open up and answer questions that are often complex. There are no right or wrong answers. The subject might not even know how to answer the questions honestly. Questions such as “How did society’s view of alcohol consumption influence your decision whether or not to take your first sip of alcohol?” or “Did you feel that the divorce of your parents would put a social stigma on your family?” involve so many factors that the answers are difficult to categorize. A researcher needs to avoid steering or prompting the subject to respond in a specific way; otherwise, the results will prove to be unreliable. And, obviously, a sociological interview is not an interrogation. The researcher will benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Experiments

You’ve probably tested personal social theories. “If I study at night and review in the morning, I’ll improve my retention skills.” Or, “If I stop drinking soda, I’ll feel better.” Cause and effect. If this, then that. When you test the theory, your results either prove or disprove your hypothesis. One way researchers test social theories is by conducting an experiment , meaning they investigate relationships to test a hypothesis—a scientific approach. There are two main types of experiments: lab-based experiments and natural or field experiments.

In a lab setting, the research can be controlled so that perhaps more data can be recorded in a certain amount of time. In a natural or field-based experiment, the generation of data cannot be controlled but the information might be considered more accurate since it was collected without interference or intervention by the researcher. As a research method, either type of sociological experiment is useful for testing if-then statements: if a particular thing happens, then another particular thing will result.

To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables. Classically, the sociologist selects a set of people with similar characteristics, such as age, class, race, or education. Those people are divided into two groups. One is the experimental group and the other is the control group . The experimental group is exposed to the independent variable(s) and the control group is not. This is similar to pharmaceutical drug trials in which the experimental group is given the test drug and the control group is given a placebo or sugar pill. To test the benefits of tutoring, for example, the sociologist might expose the experimental group of students to tutoring while the control group does not receive tutoring. Then both groups would be tested for differences in performance to see if tutoring had an effect on the experimental group of students. As you can imagine, in a case like this, the researcher would not want to jeopardize the accomplishments of either group of students, so the setting would be somewhat artificial. The test would not be for a grade reflected on their permanent record, for example.

The Stanford Prison Experiment is perhaps one of the most famous sociological experiments ever conducted. In 1971, 24 healthy, middle-class male university students were selected to take part in a simulated jail environment to examine the effects of social setting and social roles on individual psychology and behaviour. They were randomly divided into 12 guards and 12 prisoners. The prisoner subjects were arrested at home and transported blindfolded to the simulated prison in the basement of the psychology building on the campus of Stanford University. Within a day of arriving the prisoners and the guards began to display signs of trauma and sadism respectively. After some prisoners revolted by blockading themselves in their cells, the guards resorted to using increasingly humiliating and degrading tactics to control the prisoners through psychological manipulation. The experiment had to be abandoned after only six days because the abuse had grown out of hand (Haney, Banks, and Zimbardo 1973). While the insights into the social dynamics of authoritarianism it generated were fascinating, the Stanford Prison Experiment also serves as an example of the ethical issues that emerge when experimenting on human subjects.

Making Connections: Sociological Research

An experiment in action: mincome.

A real-life example will help illustrate the experimental process in sociology. Between 1974 and 1979 an experiment was conducted in the small town of Dauphin, Manitoba (the “garden capital of Manitoba”). Each family received a modest monthly guaranteed income—a “mincome”—equivalent to a maximum of 60 percent of the “low-income cut-off figure” (a Statistics Canada measure of poverty, which varies with family size). The income was 50 cents per dollar less for families who had incomes from other sources. Families earning over a certain income level did not receive mincome. Families that were already collecting welfare or unemployment insurance were also excluded. The test families in Dauphin were compared with control groups in other rural Manitoba communities on a range of indicators such as number of hours worked per week, school performance, high school dropout rates, and hospital visits (Forget 2011). A guaranteed annual income was seen at the time as a less costly, less bureaucratic public alternative for addressing poverty than the existing employment insurance and welfare programs. Today it is an active proposal being considered in Switzerland (Lowrey 2013).

Intuitively, it seems logical that lack of income is the cause of poverty and poverty-related issues. One of the main concerns, however, was whether a guaranteed income would create a disincentive to work. The concept appears to challenge the principles of the Protestant work ethic (see the discussion of Max Weber in Chapter 1). The study did find very small decreases in hours worked per week: about 1 percent for men, 3 percent for wives, and 5 percent for unmarried women. Forget (2011) argues this was because the income provided an opportunity for people to spend more time with family and school, especially for young mothers and teenage girls. There were also significant social benefits from the experiment, including better test scores in school, lower high school dropout rates, fewer visits to hospital, fewer accidents and injuries, and fewer mental health issues.

Ironically, due to lack of guaranteed funding (and lack of political interest by the late 1970s), the data and results of the study were not analyzed or published until 2011. The data were archived and sat gathering dust in boxes. The mincome experiment demonstrated the benefits that even a modest guaranteed annual income supplement could have on health and social outcomes in communities. People seem to live healthier lives and get a better education when they do not need to worry about poverty. In her summary of the research, Forget notes that the impact of the income supplement was surprisingly large given that at any one time only about a third of the families were receiving the income and, for some families, the income amount would have been very small. The income benefit was largest for low-income working families but the research showed that the entire community profited. The improvement in overall health outcomes for the community suggest that a guaranteed income would also result in savings for the public health system.

Field Research

The work of sociology rarely happens in limited, confined spaces. Sociologists seldom study subjects in their own offices or laboratories. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment without doing a lab experiment or a survey. It is a research method suited to an interpretive approach rather than to positivist approaches. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In fieldwork, the sociologists, rather than the subjects, are the ones out of their element. The researcher interacts with or observes a person or people, gathering data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or a care home, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviours in that setting. Fieldwork is optimal for observing how people behave. It is less useful, however, for developing causal explanations of why they behave that way. From the small size of the groups studied in fieldwork, it is difficult to make predictions or generalizations to a larger population. Similarly, there are difficulties in gaining an objective distance from research subjects. It is difficult to know whether another researcher would see the same things or record the same data. We will look at three types of field research: participant observation, ethnography, and the case study.

Making Connections: Sociology in the Real World

When is sharing not such a good idea.

Choosing a research methodology depends on a number of factors, including the purpose of the research and the audience for whom the research is intended. If we consider the type of research that might go into producing a government policy document on the effectiveness of safe injection sites for reducing the public health risks of intravenous drug use, we would expect public administrators to want “hard” (i.e., quantitative) evidence of high reliability to help them make a policy decision. The most reliable data would come from an experimental or quasi-experimental research model in which a control group can be compared with an experimental group using quantitative measures.

This approach has been used by researchers studying InSite in Vancouver (Marshall et al. 2011; Wood et al. 2006). InSite is a supervised safe-injection site where heroin addicts and other intravenous drug users can go to inject drugs in a safe, clean environment. Clean needles are provided and health care professionals are on hand to intervene in the case of overdose or other medical emergency. It is a controversial program both because heroin use is against the law (the facility operates through a federal ministerial exemption) and because the heroin users are not obliged to quit using or seek therapy. To assess the effectiveness of the program, researchers compared the risky usage of drugs in populations before and after the opening of the facility and geographically near and distant to the facility. The results from the studies have shown that InSite has reduced both deaths from overdose and risky behaviours, such as the sharing of needles, without increasing the levels of crime associated with drug use and addiction.

On the other hand, if the research question is more exploratory (for example, trying to discern the reasons why individuals in the crack smoking subculture engage in the risky activity of sharing pipes), the more nuanced approach of fieldwork is more appropriate. The research would need to focus on the subcultural context, rituals, and meaning of sharing pipes, and why these phenomena override known health concerns. Graduate student Andrew Ivsins at the University of Victoria studied the practice of sharing pipes among 13 habitual users of crack cocaine in Victoria, B.C. (Ivsins 2010). He met crack smokers in their typical setting downtown and used an unstructured interview method to try to draw out the informal norms that lead to sharing pipes. One factor he discovered was the bond that formed between friends or intimate partners when they shared a pipe. He also discovered that there was an elaborate subcultural etiquette of pipe use that revolved around the benefit of getting the crack resin smokers left behind. Both of these motives tended to outweigh the recognized health risks of sharing pipes (such as hepatitis) in the decision making of the users. This type of research was valuable in illuminating the unknown subcultural norms of crack use that could still come into play in a harm reduction strategy such as distributing safe crack kits to addicts.

Participant Observation

In 2000, a comic writer named Rodney Rothman wanted an insider’s view of white-collar work. He slipped into the sterile, high-rise offices of a New York “dot com” agency. Every day for two weeks, he pretended to work there. His main purpose was simply to see if anyone would notice him or challenge his presence. No one did. The receptionist greeted him. The employees smiled and said good morning. Rothman was accepted as part of the team. He even went so far as to claim a desk, inform the receptionist of his whereabouts, and attend a meeting. He published an article about his experience in The New Yorker called “My Fake Job” (2000). Later, he was discredited for allegedly fabricating some details of the story and The New Yorker issued an apology. However, Rothman’s entertaining article still offered fascinating descriptions of the inside workings of a “dot com” company and exemplified the lengths to which a sociologist will go to uncover material.

Rothman had conducted a form of study called participant observation , in which researchers join people and participate in a group’s routine activities for the purpose of observing them within that context. This method lets researchers study a naturally occurring social activity without imposing artificial or intrusive research devices, like fixed questionnaire questions, onto the situation. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behaviour. Researchers temporarily put themselves into “native” roles and record their observations. A researcher might work as a waitress in a diner, or live as a homeless person for several weeks, or ride along with police officers as they patrol their regular beat. Often, these researchers try to blend in seamlessly with the population they study, and they may not disclose their true identity or purpose if they feel it would compromise the results of their research.

At the beginning of a field study, researchers might have a question: “What really goes on in the kitchen of the most popular diner on campus?” or “What is it like to be homeless?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside. Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in shaping data into results. In a study of small-town America conducted by sociological researchers John S. Lynd and Helen Merrell Lynd, the team altered their purpose as they gathered data. They initially planned to focus their study on the role of religion in American towns. As they gathered observations, they realized that the effect of industrialization and urbanization was the more relevant topic of this social group. The Lynds did not change their methods, but they revised their purpose. This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd and Lynd 1959).

The Lynds were upfront about their mission. The townspeople of Muncie, Indiana, knew why the researchers were in their midst. But some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviours of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behaviour. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job. Once inside a group, some researchers spend months or even years pretending to be one of the people they are observing. However, as observers, they cannot get too involved. They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the end results are often descriptive or interpretive. The researcher might present findings in an article or book, describing what he or she witnessed and experienced.

This type of research is what journalist Barbara Ehrenreich conducted for her book Nickel and Dimed . One day over lunch with her editor, as the story goes, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered. Someone should do a study. To her surprise, her editor responded, Why don’t you do it? That is how Ehrenreich found herself joining the ranks of the low-wage service sector. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter. She discovered the obvious: that it’s almost impossible to get by on minimum wage work. She also experienced and observed attitudes many middle- and upper-class people never think about. She witnessed firsthand the treatment of service work employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

Ethnography

Ethnography is the extended observation of the social perspective and cultural values of an entire social setting. Researchers seek to immerse themselves in the life of a bounded group, by living and working among them. Often ethnography involves participant observation, but the focus is the systematic observation of an entire community.

The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a community. An ethnographic study might observe, for example, a small Newfoundland fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or Disney World. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a determined amount of time studying every aspect of the chosen place, taking in as much as possible, and keeping careful notes on his or her observations.

A sociologist studying a tribe in the Amazon might learn the language, watch the way villagers go about their daily lives, ask individuals about the meaning of different aspects of activity, study the group’s cosmology and then write a paper about it. To observe a spiritual retreat centre, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record how people experience spirituality in this setting, and collate the material into results.

The Feminist Perspective: Institutional Ethnography

Dorothy Smith elaborated on traditional ethnography to develop what she calls institutional ethnography (2005). In modern society the practices of everyday life in any particular local setting are often organized at a level that goes beyond what an ethnographer might observe directly. Everyday life is structured by “extralocal,” institutional forms; that is, by the practices of institutions that act upon people from a distance. It might be possible to conduct ethnographic research on the experience of domestic abuse by living in a women’s shelter and directly observing and interviewing victims to see how they form an understanding of their situation. However, to the degree that the women are seeking redress through the criminal justice system a crucial element of the situation would be missing. In order to activate a response from the police or the courts, a set of standard legal procedures must be followed, a “case file” must be opened, legally actionable evidence must be established, forms filled out, etc. All of this allows criminal justice agencies to organize and coordinate the response.

The urgent and immediate experience of the domestic abuse victims needs to be translated into a format that enables distant authorities to take action. Often this is a frustrating and mysterious process in which the immediate needs of individuals are neglected so that needs of institutional processes are met. Therefore to research the situation of domestic abuse victims, an ethnography needs to somehow operate at two levels: the close examination of the local experience of particular women and the simultaneous examination of the extralocal, institutional world through which their world is organized. In order to accomplish this, institutional ethnography focuses on the study of the way everyday life is coordinated through “textually mediated” practices: the use of written documents, standardized bureaucratic categories, and formalized relationships (Smith 1990).

Institutional paperwork translates the specific details of locally lived experience into a standardized format that enables institutions to apply the institution’s understandings, regulations, and operations in different local contexts. The study of these textual practices reveal otherwise inaccessible processes that formal organizations depend on: their formality, their organized character, and their ongoing methods of coordination, etc. An institutional ethnography often begins by following the paper trail that emerges when people interact with institutions: how does a person formulate a narrative about what has happened to him or her in a way that the institution will recognize? How is it translated into the abstract categories on a form or screen that enable an institutional response to be initiated? What is preserved in the translation to paperwork and what is lost? Where do the forms go next? What series of “processing interchanges” take place between different departments or agencies through the circulation of paperwork? How is the paperwork modified and made actionable through this process (e.g., an incident report, warrant request, motion for continuance)?

Smith’s insight is that the shift from the locally lived experience of individuals to the extralocal world of institutions is nothing short of a radical metaphysical shift in worldview. In institutional worlds, meanings are detached from directly lived processes and reconstituted in an organizational time, space, and consciousness that is fundamentally different from their original reference point. For example, the crisis that has led to a loss of employment becomes a set of anonymous criteria that determines one’s eligibility for Employment Insurance.

The unique life of a disabled child becomes a checklist that determines the content of an “individual education program” in the school system, which in turn determines whether funding will be provided for special aid assistants or therapeutic programs. Institutions put together a picture of what has occurred that is not at all the same as what was lived. The ubiquitous but obscure mechanism by which this is accomplished is textually mediated communication . The goal of institutional ethnography therefore is to making “documents or texts visible as constituents of social relations” (Smith 1990). Institutional ethnography is very useful as a critical research strategy. It is an analysis that gives grassroots organizations, or those excluded from the circles of institutional power, a detailed knowledge of how the administrative apparatuses actually work. This type of research enables more effective actions and strategies for change to be pursued.

The Case Study

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, engages in direct observation, and even participant observation, if possible. Researchers might use this method to study a single case of, for example, a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that a developed study of a single case, while offering depth on a topic, does not provide enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can add tremendous knowledge to a certain discipline. For example, a feral child, also called “wild child,” is one who grows up isolated from human beings. Feral children grow up without social contact and language, elements crucial to a “civilized” child’s development. These children mimic the behaviours and movements of animals, and often invent their own language. There are only about 100 cases of “feral children” in the world. As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” child development. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject. At age three, a Ukrainian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, eating raw meat and scraps. Five years later, a neighbour called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviours, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2006). Case studies like this offer a way for sociologists to collect data that may not be collectable by any other method.

Secondary Data or Textual Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data or textual analysis . Secondary data do not result from firsthand research collected from primary sources, but are drawn from the already-completed work of other researchers. Sociologists might study texts written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines from any period in history. Using available information not only saves time and money, but it can add depth to a study. Sociologists often interpret findings in a new way, a way that was not part of an author’s original purpose or intention. To study how women were encouraged to act and behave in the 1960s, for example, a researcher might watch movies, televisions shows, and situation comedies from that period. Or to research changes in behaviour and attitudes due to the emergence of television in the late 1950s and early 1960s, a sociologist would rely on new interpretations of secondary data. Decades from now, researchers will most likely conduct similar studies on the advent of mobile phones, the Internet, or Facebook.

One methodology that sociologists employ with secondary data is content analysis. Content analysis is a quantitative approach to textual research that selects an item of textual content (i.e., a variable) that can be reliably and consistently observed and coded, and surveys the prevalence of that item in a sample of textual output. For example, Gilens (1996) wanted to find out why survey research shows that the American public substantially exaggerates the percentage of African Americans among the poor. He examined whether media representations influence public perceptions and did a content analysis of photographs of poor people in American news magazines. He coded and then systematically recorded incidences of three variables: (1) Race: white, black, indeterminate; (2) Employed: working, not working; and (3) Age. Gilens discovered that not only were African Americans markedly overrepresented in news magazine photographs of poverty, but that the photos also tended to underrepresent “sympathetic” subgroups of the poor—the elderly and working poor—while overrepresenting less sympathetic groups—unemployed, working age adults. Gilens concluded that by providing a distorted representation of poverty, U.S. news magazines “reinforce negative stereotypes of blacks as mired in poverty and contribute to the belief that poverty is primarily a ‘black problem’” (1996).

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like Statistics Canada or the World Health Organization, publish studies with findings that are useful to sociologists. A public statistic that measures inequality of incomes might be useful for studying who benefited and who lost as a result of the 2008 recession; a demographic profile of different immigrant groups might be compared with data on unemployment to examine the reasons why immigration settlement programs are more effective for some communities than for others. One of the advantages of secondary data is that it is nonreactive (or unobtrusive) research, meaning that it does not include direct contact with subjects and will not alter or influence people’s behaviours. Unlike studies requiring direct contact with people, using previously published data does not require entering a population and the investment and risks inherent in that research process. Using available data does have its challenges. Public records are not always easy to access. A researcher needs to do some legwork to track them down and gain access to records. In some cases there is no way to verify the accuracy of existing data. It is easy, for example, to count how many drunk drivers are pulled over by the police. But how many are not? While it’s possible to discover the percentage of teenage students who drop out of high school, it might be more challenging to determine the number who return to school or get their GED later.

Another problem arises when data are unavailable in the exact form needed or do not include the precise angle the researcher seeks. For example, the salaries paid to professors at universities is often published. But the separate figures do not necessarily reveal how long it took each professor to reach the salary range, what their educational backgrounds are, or how long they have been teaching. In his research, sociologist Richard Sennett uses secondary data to shed light on current trends. In The Craftsman (2008), he studied the human desire to perform quality work, from carpentry to computer programming. He studied the line between craftsmanship and skilled manual labour. He also studied changes in attitudes toward craftsmanship that occurred not only during and after the Industrial Revolution, but also in ancient times. Obviously, he could not have firsthand knowledge of periods of ancient history; he had to rely on secondary data for part of his study. When conducting secondary data or textual analysis, it is important to consider the date of publication of an existing source and to take into account attitudes and common cultural ideals that may have influenced the research. For example, Robert S. Lynd and Helen Merrell Lynd gathered research for their book Middletown: A Study in Modern American Culture in the 1920s. Attitudes and cultural norms were vastly different then than they are now. Beliefs about gender roles, race, education, and work have changed significantly since then. At the time, the study’s purpose was to reveal the truth about small American communities. Today, it is an illustration of 1920s attitudes and values.

Sociologists conduct studies to shed light on human behaviours. Knowledge is a powerful tool that can be used toward positive change. And while a sociologist’s goal is often simply to uncover knowledge rather than to spur action, many people use sociological studies to help improve people’s lives. In that sense, conducting a sociological study comes with a tremendous amount of responsibility. Like any researchers, sociologists must consider their ethical obligation to avoid harming subjects or groups while conducting their research. The Canadian Sociological Association, or CSA, is the major professional organization of sociologists in Canada. The CSA is a great resource for students of sociology as well.

The CSA maintains a code of ethics —formal guidelines for conducting sociological research—consisting of principles and ethical standards to be used in the discipline. It also describes procedures for filing, investigating, and resolving complaints of unethical conduct. These are in line with the Tri-Council Policy Statement on Ethical Conduct for Research Involving Humans (2010) , which applies to any research with human subjects funded by one of the three federal research agencies – the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), and the Social Sciences and Humanities Research Council of Canada (SSHRC).

Practising sociologists and sociology students have a lot to consider. Some of the guidelines state that researchers must try to be skillful and fair-minded in their work, especially as it relates to their human subjects. Researchers must obtain participants’ informed consent, and inform subjects of the responsibilities and risks of research before they agree to participate. During a study, sociologists must ensure the safety of participants and immediately stop work if a subject becomes potentially endangered on any level. Researchers are required to protect the privacy of research participants whenever possible. Even if pressured by authorities, such as police or courts, researchers are not ethically allowed to release confidential information. Researchers must make results available to other sociologists, must make public all sources of financial support, and must not accept funding from any organization that might cause a conflict of interest or seek to influence the research results for its own purposes. The CSA’s ethical considerations shape not only the study but also the publication of results.

Pioneer German sociologist Max Weber (1864–1920) identified another crucial ethical concern. Weber understood that personal values could distort the framework for disclosing study results. While he accepted that some aspects of research design might be influenced by personal values, he declared it was entirely inappropriate to allow personal values to shape the interpretation of the responses. Sociologists, he stated, must establish value neutrality , a practice of remaining impartial, without bias or judgment, during the course of a study and in publishing results (1949). Sociologists are obligated to disclose research findings without omitting or distorting significant data. Value neutrality does not mean having no opinions. It means striving to overcome personal biases, particularly subconscious biases, when analyzing data. It means avoiding skewing data in order to match a predetermined outcome that aligns with a particular agenda, such as a political or moral point of view. Investigators are ethically obligated to report results, even when they contradict personal views, predicted outcomes, or widely accepted beliefs. Is value neutrality possible?

Many sociologists believe it is impossible to set aside personal values and retain complete objectivity. Individuals inevitably see the world from a partial perspective. Their interests are central to the types of topics they choose, the types of questions they ask, the way they frame their research and the research methodologies they select to pursue it. Moreover, facts, however objective, do not exist in a void. As we noted in Chapter 1, Jürgen Habermas (1972) argues that sociological research has built-in interests quite apart from the personal biases of individual researchers. Positivist sociology has an interest in pursuing types of knowledge that are useful for controlling and administering social life. Interpretive sociology has an interest in pursuing types of knowledge that promote greater mutual understanding and the possibility of consensus among members of society. Critical sociology has an interest in types of knowledge that enable emancipation from power relations and forms of domination in society. In Habermas’ view, sociological knowledge is not disinterested knowledge. This does not discredit the results of sociological research but allows readers to take into account the perspective of the research when judging the validity and applicability of its outcomes.

case study in-depth analysis of a single event, situation, or individual

code of ethics a set of guidelines that the Canadian Sociological Association has established to foster ethical research and professionally responsible scholarship in sociology

content analysis a quantitative approach to textual research that selects an item of textual content that can be reliably and consistently observed and coded, and surveys the prevalence of that item in a sample of textual output

control group an experimental group that is not exposed to the independent variable

correlation when a change in one variable coincides with a change in another variable, but does not necessarily indicate causation

d ependent variable variable changed by another variable

empirical evidence evidence corroborated by direct experience and/or observation

ethnography observing a complete social setting and all that it entails

experiment the testing of a hypothesis under controlled conditions

field research gathering data from a natural environment without doing a lab experiment or a survey

Hawthorne effect when study subjects behave in a certain manner due to their awareness of being observed by a researcher

hypothesis an educated guess with predicted outcomes about the relationship between two or more variables hypothetico-deductive methodologies methodologies based on deducing a prediction from a hypothesis and testing the  validity of the hypothesis by whether it correctly predicts observations

independent variable  variable that causes change in a dependent variable

inductive approach methodologies that derive a general statement from a series of empirical observations

institutional ethnography the study of the way everyday life is coordinated through institutional, textually mediated practices

interpretive approach a sociological research approach that seeks in-depth understanding of a topic or subject through observation or interaction

interview  a one-on-one conversation between a researcher and a subject

literature review a scholarly research step that entails identifying and studying all existing studies on a topic to create a basis for new research

nonreactive  unobtrusive research that does not include direct contact with subjects and will not alter or influence people’s behaviours

operational definitions specific explanations of abstract concepts that a researcher plans to study

participant observation immersion by a researcher in a group or social setting in order to make observations from an “insider” perspective

population a defined group serving as the subject of a study

positivist approach a research approach based on the natural science model of knowledge utilizing a hypothetico-deductive formulation of the research question and quantitative data

primary data data collected directly from firsthand experience

qualitative data  information based on interpretations of meaning

quantitative data information from research collected in numerical form that can be counted

random sample a study’s participants being randomly selected to serve as a representation of a larger population reliability a measure of a study’s consistency that considers how likely results are to be replicated if a study is reproduced research design a detailed, systematic method for conducting research and obtaining data

sample small, manageable number of subjects that represent the population

scientific method a systematic research method that involves asking a question, researching existing sources, forming a hypothesis, designing and conducting a study, and drawing conclusions

secondary data analysis using data collected by others but applying new interpretations

surveys data collections from subjects who respond to a series of questions about behaviours and opinions, often in the form of a questionnaire

textually mediated communication institutional forms of communication that rely on written documents, texts, and paperwork

validity the degree to which a sociological measure accurately reflects the topic of study

value neutrality a practice of remaining impartial, without bias or judgment during the course of a study and in publishing results

variable a characteristic or measure of a social phenomenon that can take different values

Section Summary

2.1. Approaches to Sociological Research Using the scientific method, a researcher conducts a study in five phases: asking a question, researching existing sources, formulating a hypothesis, conducting a study, and drawing conclusions. The scientific method is useful in that it provides a clear method of organizing a study. Some sociologists conduct scientific research through a positivist framework utilizing a hypothetico-deductive formulation of the research question. Other sociologists conduct scientific research by employing an interpretive framework that is often inductive in nature. Scientific sociological studies often observe relationships between variables. Researchers study how one variable changes another. Prior to conducting a study, researchers are careful to apply operational definitions to their terms and to establish dependent and independent variables.

2.2. Research Methods Sociological research is a fairly complex process. As you can see, a lot goes into even a simple research design. There are many steps and much to consider when collecting data on human behaviour, as well as in interpreting and analyzing data in order to form conclusive results. Sociologists use scientific methods for good reason. The scientific method provides a system of organization that helps researchers plan and conduct the study while ensuring that data and results are reliable, valid, and objective. The many methods available to researchers—including experiments, surveys, field studies, and secondary data analysis—all come with advantages and disadvantages. The strength of a study can depend on the choice and implementation of the appropriate method of gathering research. Depending on the topic, a study might use a single method or a combination of methods. It is important to plan a research design before undertaking a study. The information gathered may in itself be surprising, and the study design should provide a solid framework in which to analyze predicted and unpredicted data.

Table 2.2. Main Sociological Research Methods. Sociological research methods have advantages and disadvantages.

2.3. Ethical Concerns Sociologists and sociology students must take ethical responsibility for any study they conduct. They must first and foremost guarantee the safety of their participants. Whenever possible, they must ensure that participants have been fully informed before consenting to be part of a study. The CSA (Canadian Sociological Association) maintains ethical guidelines that sociologists must take into account as they conduct research. The guidelines address conducting studies, properly using existing sources, accepting funding, and publishing results. Sociologists must try to maintain value neutrality. They must gather and analyze data objectively, setting aside their personal preferences, beliefs, and opinions. They must report findings accurately, even if they contradict personal convictions.

Section Quiz

2.1. Approaches to Sociological Research 1. A measurement is considered ______­ if it actually measures what it is intended to measure, according to the topic of the study.

• sociological
• quantitative

2. Sociological studies test relationships in which change in one ______ causes change in another.

• test subject
• operational definition

3. In a study, a group of 10-year-old boys are fed doughnuts every morning for a week and then weighed to see how much weight they gained. Which factor is the dependent variable?

• the doughnuts
• the duration of a week
• the weight gained

4. Which statement provides the best operational definition of “childhood obesity”?

• children who eat unhealthy foods and spend too much time watching television and playing video games
• a distressing trend that can lead to health issues including type 2 diabetes and heart disease
• body weight at least 20 percent higher than a healthy weight for a child of that height
• the tendency of children today to weigh more than children of earlier generations

2.2. Research Methods 5. Which materials are considered secondary data?

• photos and letters given to you by another person
• books and articles written by other authors about their studies
• information that you have gathered and now have included in your results
• responses from participants whom you both surveyed and interviewed

6. What method did Andrew Ivsins use to study crack users in Victoria?

• field research
• content analysis

7. Why is choosing a random sample an effective way to select participants?

• Participants do not know they are part of a study
• The researcher has no control over who is in the study
• It is larger than an ordinary sample
• Everyone has the same chance of being part of the study

8. What research method did John S. Lynd and Helen Merrell Lynd mainly use in their Middletown study?

• secondary data
• participant observation

9. Which research approach is best suited to the positivist approach?

• questionnaire
• ethnography
• secondary data analysis

10. The main difference between ethnography and other types of participant observation is:

• ethnography isn’t based on hypothesis testing
• ethnography subjects are unaware they’re being studied
• ethnographic studies always involve minority ethnic groups
• there is no difference

11. Which best describes the results of a case study?

• it produces more reliable results than other methods because of its depth
• its results are not generally applicable
• it relies solely on secondary data analysis
• all of the above

12. Using secondary data is considered an unobtrusive or ________ research method.

• nonreactive
• nonparticipatory
• nonrestrictive
• nonconfrontive

2.3. Ethical Concerns 13. Which statement illustrates value neutrality?

• Obesity in children is obviously a result of parental neglect and, therefore, schools should take a greater role to prevent it.
• In 2003, states like Arkansas adopted laws requiring elementary schools to remove soft drink vending machines from schools.
• Merely restricting children’s access to junk food at school is not enough to prevent obesity.
• Physical activity and healthy eating are a fundamental part of a child’s education.

14. Which person or organization defined the concept of value neutrality?

• Institutional Review Board (IRB)
• Peter Rossi
• Canadian Sociological Association (CSA)

15. To study the effects of fast food on lifestyle, health, and culture, from which group would a researcher ethically be unable to accept funding?

• a fast-food restaurant
• a nonprofit health organization
• a private hospital
• a governmental agency like Health and Social Services

Short Answer

• Write down the first three steps of the scientific method. Think of a broad topic that you are interested in and which would make a good sociological study—for example, ethnic diversity in a college, homecoming rituals, athletic scholarships, or teen driving. Now, take that topic through the first steps of the process. For each step, write a few sentences or a paragraph: 1) Ask a question about the topic. 2) Do some research and write down the titles of some articles or books you’d want to read about the topic. 3) Formulate a hypothesis.

2.2.Research Methods

• What type of data do surveys gather? For what topics would surveys be the best research method? What drawbacks might you expect to encounter when using a survey? To explore further, ask a research question and write a hypothesis. Then create a survey of about six questions relevant to the topic. Provide a rationale for each question. Now define your population and create a plan for recruiting a random sample and administering the survey.
• Imagine you are about to do field research in a specific place for a set time. Instead of thinking about the topic of study itself, consider how you, as the researcher, will have to prepare for the study. What personal, social, and physical sacrifices will you have to make? How will you manage your personal effects? What organizational equipment and systems will you need to collect the data?
• Create a brief research design about a topic in which you are passionately interested. Now write a letter to a philanthropic or grant organization requesting funding for your study. How can you describe the project in a convincing yet realistic and objective way? Explain how the results of your study will be a relevant contribution to the body of sociological work already in existence.
• Why do you think the CSA crafted such a detailed set of ethical principles? What type of study could put human participants at risk? Think of some examples of studies that might be harmful. Do you think that, in the name of sociology, some researchers might be tempted to cross boundaries that threaten human rights? Why?
• Would you willingly participate in a sociological study that could potentially put your health and safety at risk, but had the potential to help thousands or even hundreds of thousands of people? For example, would you participate in a study of a new drug that could cure diabetes or cancer, even if it meant great inconvenience and physical discomfort for you or possible permanent damage?

Further Research

2.1. Approaches to Sociological Research For a historical perspective on the scientific method in sociology, read “The Elements of Scientific Method in Sociology” by F. Stuart Chapin (1914) in the American Journal of Sociology : http://openstaxcollege.org/l/Method-in-Sociology

2.2. Research Methods For information on current real-world sociology experiments, visit: http://openstaxcollege.org/l/Sociology-Experiments

2.3. Ethical Concerns Founded in 1966, the CSA is a nonprofit organization located in Montreal, Quebec, with a membership of 900 researchers, faculty members, students, and practitioners of sociology. Its mission is to promote “research, publication and teaching in Sociology in Canada.” Learn more about this organization at http://www.csa-scs.ca/ .

2.1. Approaches to Sociological Research Merton, Robert. 1968 [1949]. Social Theory and Social Structure . New York: Free Press.

2.2. Research Methods Forget, Evelyn. 2011. “The Town with no Poverty: Using Health Administration Data to Revisit Outcomes of a Canadian Guaranteed Annual Income Field Experiement.” Canadian Public Policy . 37(3): 282-305.

Franke, Richard and James Kaul. 1978. “The Hawthorne Experiments: First Statistical Interpretation.” American Sociological Review 43(5):632–643.

Gilens, Martin. 1996. “Race and Poverty in America: Public Misperceptions and the American News Media.” The Public Opinion Quarterly 60(4):515–541. Grice, Elizabeth. 2006. “Cry of an Enfant Sauvage.” The Telegraph . Retrieved July 20, 2011 ( http://www.telegraph.co.uk/culture/tvandradio/3653890/Cry-of-an-enfant-sauvage.html ).

Haney, C., Banks, W. C., and Zimbardo, P. G. 1973. “Interpersonal Dynamics in a Simulated Prison.” International Journal of Criminology and Penology  1:69–97.

Ivsins, A.K. 2010. “’Got a pipe?’ The social dimensions and functions of crack pipe sharing among crack users in Victoria, BC.” MA thesis, Department of Sociology, University of Victoria. Retrieved February 14, 2014 ( http://dspace.library.uvic.ca:8080/bitstream/handle/1828/3044/Full%20thesis%20Ivsins_CPS.2010_FINAL.pdf?sequence=1 )

Lowrey, Annie. 2013. “Switzerland’s Proposal to Pay People for Being Alive.” The  New York Times Magazine. Retrieved February 17, 2014 ( http://www.nytimes.com/2013/11/17/magazine/switzerlands-proposal-to-pay-people-for-being-alive.html?pagewanted=1&_r=2 ).

Lynd, Robert S. and Helen Merrell Lynd. 1959. Middletown: A Study in Modern American Culture . San Diego, CA: Harcourt Brace Javanovich.

Lynd, Staughton. 2005. “Making Middleton.” Indiana Magazine of History 101(3):226–238.

Marshall, B.D.L., M.J. Milloy,  E. Wood, J.S.G.  Montaner,  and T. Kerr. 2011. “Reduction in overdose mortality after the opening of North America’s first medically supervised safer injecting facility: A retrospective population-based study.” Lancet  377(9775):1429–1437.

Rothman, Rodney. 2000. “My Fake Job.” The New Yorker , November 27, 120.

Sennett, Richard. 2008. The Craftsman . New Haven, CT: Yale University Press. Retrieved July 18, 2011 ( http://www.richardsennett.com/site/SENN/Templates/General.aspx?pageid=40 ).

Smith, Dorothy. 1990. “Textually Mediated Social Organization” Pp. 209–234 in Texts, Facts and Femininity: Exploring the Relations of Ruling. London: Routledge.

Smith, Dorothy. 2005. Institutional Ethnography: A Sociology for People. Toronto: Altamira Press.

Sonnenfeld, Jeffery A. 1985. “Shedding Light on the Hawthorne Studies.” Journal of Occupational Behavior 6:125.

Wood, E., M.W. Tyndall, J.S. Montaner, and T. Kerr. 2006. “Summary of findings from the evaluation of a pilot medically supervised safer injecting facility.” Canadian Medical Association Journal  175(11):1399–1404.

2.3. Ethical Concerns Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada, and Social Sciences and Humanities Research Council of Canada. 2010.  Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans . Retrieved February 15, 2014 ( http://www.pre.ethics.gc.ca/pdf/eng/tcps2/TCPS_2_FINAL_Web.pdf ).

Canadian Sociological Association. 2012. Statement of Professional Ethics . Retrieved February 15, 2014 ( http://www.csa-scs.ca/files/www/csa/documents/codeofethics/2012Ethics.pdf ).

Habermas, Jürgen. 1972. Knowledge and Human Interests. Boston: Beacon Press

Weber, Max. 1949. Methodology of the Social Sciences . Translated by H. Shils and E. Finch. Glencoe, IL: Free Press.

Solutions to Section Quiz

1. C | 2. C | 3. D | 4. C | 5. B | 6. C | 7. D | 8. C | 9. A | 10. A | 11. B | 12. A | 13. B | 14. D | 15. A

Image Attributions

Figure 2.3.  Didn’t they abolish the mandatory census? Then what’s this? by  Khosrow Ebrahimpour ( https://www.flickr.com/photos/xosrow/5685345306/in/photolist-9EoT5W-ow4tdu-oeGG4m-oeMEcK-oy2jM2-ovJC8w-oePSRQ-9J2V24-of1Hnu-of243u-of2K2B-of2FHn-owiBSA-owtQN3-of1Ktd-oitLSC-oeVJte-oep8KX-ovEz8w-oeohhF-oew5Xb-oewdWN-owavju-oeMEnV-oweLcN-ovEPGG-ovAQUX-oeo2eL-oeo3Fd-oeoqxh-oxCKnv-ovEzA5-oewFHa-ovHRSz-ow8QtY-oeQY6Y-oeZReR-oeQmHw-oeKXid-oeQLKa-oy6fNT-ow4sVT-oeQMQq-oeQPPr-oeQYbL-ow8hS1-ow4n8v-owiPKS-oeQF41-oeiH5z ) used under CC BY 2.0 ( https://creativecommons.org/licenses/by/2.0/ )

Figure 2.4. Dauphin Canadian Northern Railway Station by Bobak Ha’Eri ( http://commons.wikimedia.org/wiki/File:2009-0520-TrainStation-Dauphin.jpg ) used under CC BY 3.0 license ( http://creativecommons.org/licenses/by/3.0/deed.en )

Figure 2.5.  Punk Band by Patrick ( https://www.flickr.com/photos/lordkhan/181561343/in/photostream/ ) used under CC BY 2.0 ( https://creativecommons.org/licenses/by/2.0/ )

Figure 2.6.  Crack Cocaine Smokers in Vancouver Alleyway ( http://commons.wikimedia.org/wiki/File:Crack_Cocaine_Smokers_in_Vancouver_Alleyway.jpg ) is in the public domain ( http://en.wikipedia.org/wiki/Public_domain )

Figure 2.8.  Muncie, Indiana High School: 1917 by Don O’Brien ( https://www.flickr.com/photos/dok1/3694125269/ ) used under CC BY 2.0 license ( https://creativecommons.org/licenses/by/2.0/ )

Introduction to Sociology - 1st Canadian Edition Copyright © 2014 by William Little and Ron McGivern is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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A hypothesis is a statement that is then tested through research. A hypothesis usually consists of what the researcher thinks to be the case, and the purpose of the research is to discover whether she/he was correct. It is a feature of scientific research methodology . Some interpretivist sociologists prefer to use an aim rather than a hypothesis as they are not interested in replicating scientific research methods as they don't believe sociology is, or should try to be, a science.

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3.1.3: Developing Theories and Hypotheses

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2.5: Developing a Hypothesis

Learning objectives.

• Distinguish between a theory and a hypothesis.
• Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
• Understand the characteristics of a good hypothesis.

Theories and Hypotheses

Before describing how to develop a hypothesis, it is important to distinguish between a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition (1965) [1] . He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.

Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.

A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observations before we can develop a broader theory.

Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.

But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.

Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [2] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.

Theory Testing

The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers begin with a set of phenomena and either construct a theory to explain or interpret them or choose an existing theory to work with. They then make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary. This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure \(\PageIndex{1}\) shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.

As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [3] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans [Zajonc & Sales, 1966] [4] in many other studies afterward).

Incorporating Theory into Your Research

When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.

There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that it really does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.

• Zajonc, R. B. (1965). Social facilitation. Science, 149 , 269–274 ↵
• Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
• Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
• Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵

Module 1: Foundations of Sociology

The main sociological theories, learning outcomes.

• Explain sociological theories

Figure 1. Sociologists develop theories to explain social occurrences such as protest rallies. (Photo courtesy of voanews.com/Wikimedia Commons)

Sociologists study social events, interactions, and patterns, and they develop a theory in an attempt to explain why things work as they do. A sociological  theory  seeks to explain social phenomena. Theories can be used to create a testable proposition, called a hypothesis , about society (Allan 2006).

Theories vary in scope depending on the scale of the issues that they are meant to explain. Macro-level theories relate to large-scale issues and large groups of people, while micro-level theories look at very specific relationships between individuals or small groups. Grand theories attempt to explain large-scale relationships and answer fundamental questions such as why societies form and why they change. Sociological theory is constantly evolving and should never be considered complete. Classic sociological theories are still considered important and current, but new sociological theories build upon the work of their predecessors and add to them (Calhoun 2002).

In sociology, a few theories provide broad perspectives that help explain many different aspects of social life, and these are called paradigms. Paradigms are philosophical and theoretical frameworks used within a discipline to formulate theories, generalizations, and the experiments performed in support of them. Three paradigms have come to dominate sociological thinking, because they provide useful explanations: structural functionalism, conflict theory, and symbolic interactionism.

• Major Sociological Paradigms: Crash Course Sociology #2. Provided by : CrashCourse. Located at : https://www.youtube.com/watch?v=DbTt_ySTjaY . License : Other . License Terms : Standard YouTube License
• Modification, adaptation, and original content. Provided by : Lumen Learning. License : CC BY: Attribution
• Theoretical Perspectives. Authored by : OpenStax CNX. Located at : https://cnx.org/contents/[email protected]:QMRfI2p1@11/Theoretical-Perspectives . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]

Open Education Sociology Dictionary

Table of Contents

Definition of Hypothesis

( noun ) A proposed and testable explanation between two or more variables that predicts an outcome or explains a phenomenon.

Examples of Hypothesis

• Note : The  variables are the students, the time spent studying, and the test grades. To test the hypothesis, collect information from each student about how much time they spent studying prior to the test and compare that to the the testing outcomes.
• Sapir-Whorf hypothesis

Types of Hypothesis

• asymmetry hypothesis
• null hypothesis
• substantive hypothesis

Hypothesis Pronunciation

Pronunciation Usage Guide

Syllabification : hy·poth·e·sis

Audio Pronunciation

Phonetic Spelling

• American English – /hie-pAHth-uh-suhs/
• British English – /hie-pOth-i-sis/

International Phonetic Alphabet

• American English – /haɪˈpɑθəsəs/
• British English – /hʌɪˈpɒθᵻsᵻs/

Usage Notes

• Plural: hypotheses
• A hypothesis must have the capacity to be disconfirmed or proven false to have meaning. For example, “criminals” commit more crimes than “non-criminals” cannot be proven wrong.
• A hypothesis can either come from theory ( deduction ) or lead to theory ( induction ).
• A working hypothesis refers to a hypothesis that has not been thoroughly tested and verified.
• Hypothesis testing is the process of testing a hypothesis in a scientific manner that requires a link between the concepts or  variables under investigation and rigorous testing methodology .
• An ( noun ) hypothesist ( verb ) hypothesizes ( adverb ) hypothetically about social issues to create an ( adjective ) hypothetical explanation.

Related Videos

Additional Information

• Quantitative Research Resources – Books, Journals, and Helpful Links
• Word origin of “hypothesis” – Online Etymology Dictionary: etymonline.com
• Gauch, Hugh G., Jr. 2003. Scientific Method in Practice . Cambridge: Cambridge University Press.
• Lehmann, E. L., and Joseph P. Romano. 2010. Testing Statistical Hypotheses . 3rd ed. New York: Springer.
• Poletiek, Fenna. 2001. Hypothesis-testing Behaviour . Philadelphia: Psychology.
• Popper, Karl R. 1959.  The Logic of Scientific Discovery . New York: Basic Books.

Related Terms

• correlation
• dependent variable
• hypothetico-deductive model
• independent variable
• inferential statistics
• statistical analysis

Contributor: C. E. Seaman

Works Consulted

Andersen, Margaret L., and Howard Francis Taylor. 2011.  Sociology: The Essentials . 6th ed. Belmont, CA: Wadsworth.

Babbie, Earl. 2013. The Practice of Social Research . 13th ed. Belmont, CA: Wadsworth.

Bilton, Tony, Kevin Bonnett, Pip Jones, David Skinner, Michelle Stanworth, and Andrew Webster. 1996. Introductory Sociology . 3rd ed. London: Macmillan.

Branscombe, Nyla R., and Robert A. Baron. 2017. Social Psychology . 14th ed. Harlow, England: Pearson.

Brinkerhoff, David, Lynn White, Suzanne Ortega, and Rose Weitz. 2011.  Essentials of Sociology . 8th ed. Belmont, CA: Wadsworth.

Brym, Robert J., and John Lie. 2007.  Sociology: Your Compass for a New World . 3rd ed. Belmont, CA: Wadsworth.

Bryman, Alan. 2012. Social Research Methods . 4th ed. New York: Oxford University Press.

Burdess, Neil. 2010. Starting Statistics: A Short, Clear Guide . Thousand Oaks, CA: SAGE.

Cramer, Duncan, and Dennis Howitt. 2004. The SAGE Dictionary of Statistics: A Practical Resource for Students in the Social Sciences . Thousand Oaks, CA: SAGE.

Farlex. (N.d.) TheFreeDictionary.com: Dictionary, Encyclopedia and Thesaurus . Farlex. ( http://www.thefreedictionary.com/ ).

Ferrante, Joan. 2011a. Seeing Sociology: An Introduction . Belmont, CA: Wadsworth.

Ferrante, Joan. 2011b.  Sociology: A Global Perspective . 7th ed. Belmont, CA: Wadsworth.

Ferris, Kerry, and Jill Stein. 2010.  The Real World: An Introduction to Sociology . 2nd ed. New York: Norton.

Fioramonti, Lorenzo. 2014. How Numbers Rule the World: The Use and Abuse of Statistics in Global Politics . London: Zed Books.

Griffiths, Heather, Nathan Keirns, Eric Strayer, Susan Cody-Rydzewski, Gail Scaramuzzo, Tommy Sadler, Sally Vyain, Jeff Bry, Faye Jones. 2016. Introduction to Sociology 2e . Houston, TX: OpenStax.

Henslin, James M. 2012.  Sociology: A Down-to-Earth Approach . 10th ed. Boston: Allyn & Bacon.

Hughes, Michael, and Carolyn J. Kroehler. 2011.  Sociology: The Core . 10th ed. New York: McGraw-Hill.

Kendall, Diana. 2011.  Sociology in Our Times . 8th ed. Belmont, CA: Wadsworth.

Kimmel, Michael S., and Amy Aronson. 2012. Sociology Now . Boston: Allyn & Bacon.

Kornblum, William. 2008. Sociology in a Changing World . 8th ed. Belmont, CA: Wadsworth.

Larson, Ron, and Elizabeth Farber. 2015. Elementary Statistics: Picturing the World . 6th ed. Boston: Pearson.

Macionis, John. 2012.  Sociology . 14th ed. Boston: Pearson.

Macionis, John, and Kenneth Plummer. 2012.  Sociology: A Global Introduction . 4th ed. Harlow, England: Pearson Education.

O’Leary, Zina. 2007. The Social Science Jargon Buster: The Key Terms You Need to Know . Thousand Oaks, CA: SAGE.

Oxford University Press. (N.d.) Oxford Dictionaries . ( https://www.oxforddictionaries.com/ ).

Ravelli, Bruce, and Michelle Webber. 2016. Exploring Sociology: A Canadian Perspective . 3rd ed. Toronto: Pearson.

Salkind, Neil J., ed. 2007. Encyclopedia of Measurement and Statistics . Thousand Oaks, CA: SAGE.

Schaefer, Richard. 2013.  Sociology: A Brief Introduction . 10th ed. New York: McGraw-Hill.

Shepard, Jon M. 2010.  Sociology . 11th ed. Belmont, CA: Wadsworth.

Shepard, Jon M., and Robert W. Greene. 2003.  Sociology and You . New York: Glencoe.

Stolley, Kathy S. 2005.  The Basics of Sociology . Westport, CT: Greenwood Press.

Taylor & Francis. (N.d.)  Routledge Handbooks Online . ( https://www.routledgehandbooks.com/ ).

Thompson, William E., and Joseph V. Hickey. 2012.  Society in Focus: An Introduction to Sociology . 7th ed. Boston: Allyn & Bacon.

Tischler, Henry L. 2011.  Introduction to Sociology . 10th ed. Belmont, CA: Wadsworth.

Weinstein, Jay A. 2010. Applying Social Statistics: An Introduction to Quantitative Reasoning in Sociology . Lanham, MD: Rowman & Littlefield.

Wikipedia contributors. (N.d.) Wikipedia, The Free Encyclopedia . Wikimedia Foundation. ( https://en.wikipedia.org/ ).

Wikipedia contributors. (N.d.) Wiktionary, The Free Dictionary . Wikimedia Foundation. ( http://en.wiktionary.org ).

Wiley. (N.d.) Wiley Online Library . ( http://onlinelibrary.wiley.com/ ).

Cite the Definition of Hypothesis

ASA – American Sociological Association (5th edition)

Seaman, C. E. 2015. “hypothesis.” In Open Education Sociology Dictionary , edited by Kenton Bell. Retrieved May 13, 2024 ( https://sociologydictionary.org/hypothesis/ ).

APA – American Psychological Association (6th edition)

Seaman, C. E. (2015). hypothesis. In K. Bell (Ed.), Open education sociology dictionary . Retrieved from https://sociologydictionary.org/hypothesis/

Chicago/Turabian: Author-Date – Chicago Manual of Style (16th edition)

Seaman, C. E. 2015. “hypothesis.” In Open Education Sociology Dictionary , edited by Kenton Bell. Accessed May 13, 2024. https://sociologydictionary.org/hypothesis/ .

MLA – Modern Language Association (7th edition)

Seaman, C. E. “hypothesis.” Open Education Sociology Dictionary . Ed. Kenton Bell. 2015. Web. 13 May. 2024. < https://sociologydictionary.org/hypothesis/ >.

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Home >> Socio Short Notes >> Sapir-Whorf hypothesis

Sapir-Whorf hypothesis

In the 1930s, two anthropologists, Edward Sapir and Benjamin Whorf, became intrigued when they noticed that the Hopi Indians of the southwestern United States had no words to distinguish among the past, the present, and the future. English, in contrast as well as French, spanish, Swahili, and other languages distinguishes carefully among these three time frames.

From this observation, Sapir and Whorf began to think that words might be more than labels that people attach to things. Eventually, they concluded that language has embedded within it ways of looking at the world. In other words, language not only expresses our thoughts and perceptions but also shapes the way we think and perceive. When we learn a language, we learn not only words but also ways of thinking and perceiving.

The Sapir-Whorf hypothesis indicates that rather than objects and events forcing themselves onto our consciousness, it is our language that determines our consciousness, and hence our perception of objects and events.

For English speakers, the term nuts combine almonds, walnuts, and pecans in such a way that we see them as belonging together. Although Sapir and Whorf's observation that the Hopi do not have tenses was inaccurate, they did stumble onto a major truth about social life. Learning a language means not only learning words but also acquiring the perceptions embedded in that language. In other words, language both reflects and shapes our cultural experiences.

Variables, Sampling, Hypothesis, Reliability, and Validity | Sociology UPSC Notes

Table of Contents

• 1 The Variables:
• 2 Variables can be:
• 3 Experiment and factors that were measured:
• 4 Active factors and what they are:
• 5 Qualitative and numeric variables:
• 6 Sampling:
• 7 There are two reasons why sampling is done.
• 8 Why we take samples,
• 9 How to Pick a Sample:
• 10 (Sarantakos):
• 11 The benefits of sampling:
• 12 Why sampling is important:
• 13 Sample Size Problem:
• 14 Different kinds of sampling:
• 15 Probability Sampling:
• 16 Simple random sampling has the following benefits:
• 17 Random sampling with a plan:
• 18 The pros of stratified random sampling are as follows:
• 19 Non-probability sampling:
• 20 Some examples of theories are as follows:
• 21 Criteria for Building Hypotheses:
• 22 What hypotheses are:
• 23 The important hypotheses could be:
• 24 Different kinds of hypotheses:
• 25 Goode and Hatt have identified three kinds of theories based on how abstract they are:
• 26 Problems with coming up with hypotheses:
• 27 Things that make a hypothesis useful:
• 28 Where Hypotheses Come From:
• 29 What hypotheses do or how important they are:
• 30 Criticisms of Hypotheses:
• 31 Types of Validity; In social study, there are four main types of validity:
• 32 Marriage between Value and Trustworthiness

The Variables:

• A variable is something that can have more than one number. It’s not always the same. It is something that a lot of people, groups, events, things, etc. have in common.

• The degree to which each case has the trait is different from case to case. So, age (young, middle-aged, old), income class (low, middle, upper), caste (low, intermediate, high), education (illiterate, less educated, highly educated), work (low status, high status), etc. are all variables.

• The variables chosen for study are called explanatory variables, and all other variables are called extraneous variables. Variables that are not part of the set of explanatory variables are either managed or uncontrolled.

Controlled factors, also called control variables, are kept the same or kept from changing during the study. This is done so that the research can focus on one thing. For example, all men and women under the age of 18 could be left out of the study. This would mean that the theory doesn’t care about any particular subgroups.

Variables can be:

Dependent and Independent Variables:

• A variable that changes based on how another variable changes is called a “dependent variable.” A variable that changes without affecting another variable is called an independent variable. In a controlled experiment, the experimental variable that is not given to the control group is the independent variable.

• The variable that is changed by the experimenter is the independent variable. For example, a teacher might want to know if the talk method, the question-and-answer method, the visual method, or a mix of two or more of these methods is the best way to teach. In this case, the way of teaching is an independent variable that the teacher can change. The “effect on the students’ understanding” is the dependent variable. The thing we are trying to explain is called the “dependent variable.” In this experiment, apart from the ways of teaching, other independent factors could be the students’ personalities, their social class, how they are motivated (by rewards and punishments), the atmosphere in the classroom, how they feel about the teacher, and so on.

Experiment and factors that were measured:

• The experimental variables describe how the experiment was done, while the observed variables describe how the experiment was done. For example, rural development (a measured variable) could be looked at in terms of income growth, literacy rate, infrastructure, access to medical care, social security, and so on. In another study, we could look at how the absence or presence of books, libraries, good teachers, the use of visuals, and so on affects how well students do in school. All of these will be things that the researcher will change or change in an experiment. When planning and doing study, it is important to know the difference between these two types of variables.

Active factors and what they are:

• Variables that are changed or tried out will be called “active variables,” and variables that are measured will be called “assigned variables.” In other words, an active variable is one that can be changed, and a given variable is one that can’t be changed.

Qualitative and numeric variables:

• A quantitative variable is one whose values or groups are made up of numbers and whose differences between groups can be shown with numbers. Thus, age, income, sizes are quantitative factors. The qualitative variable is one that is not made up of numbers but of clear groups. This variable has at least two different groups that can be told apart. Class (low, middle, or high), caste (low, middle, or high), gender (male or female), and religion (Hindu or not Hindu) are all examples of qualitative factors.

• (Singleton and Straits) Relationships between quantitative factors can be either good or bad. When the value of one variable goes up, the value of the other variable also goes up, or when the value of one variable goes down, the value of the other variable also goes down. In other words, the two things always change in the same way. For example, if a father is taller, his kid will also be taller. A negative relationship between two variables arises when the value of one variable goes down and the value of the other variable goes up. For example, as age goes up, life expectancy goes down.

• Therese Baker has called qualitative and quantitative variables “categorical” and “numerical” variables, respectively. The former (e.g., occupation, religion, caste, gender, education, income) are made up of sets of categories (or attributes) that must follow two rules: one, the categories must be different from each other, i.e., they must be mutually exclusive; and two, the categories must be exhaustive, i.e., they should cover all the possible ranges of variation in a variable. After putting oneself into the categories of educated (the other being illiterate) in the field of education, one can put oneself into the subcategories of student, graduate, postgraduate, etc.

Variables can also be either binary or continuous. For example, sex is a binary variable, but ability is a continuous variable. Only a few factors are true dichotomies most of the time. Most variables can take on numbers that don’t change. Still, it’s good to keep in mind that converting continuous variables to dichotomous or trichotomous variables is often useful or required.

• A sample is a small group of people taken from a bigger group. It will be a good representation of the whole population only if it has the same basic traits as the whole population. In sampling, what we care about is not what kinds of units (people) will be interviewed or watched, but how many units of a certain kind and by what method should be picked.

“A sample is a part of the population that is studied to draw conclusions about the whole population,” says Manheim. In order to define the group from which the sample is taken, the “target population” and the “sampling frame” must be named. The target community is the group of people about whom information is needed. For example, drug-using students at one university, voters in one village/constituency, and so on. In order to define the group, the criteria for which cases are included and which are not must be stated.

• For example, for a study on how well women in one town know their rights, the target population is all women between the ages of 18 and 50, whether they are married or not. If the unit is an institution, like Vidya Mandir, it needs to say what kind of structure it has, how big it is based on the number of students in the school and college sections, and how many teachers and employees work in the professional classes.

• The sampling frame needs to be built so that the target group can be used. This is the set of all the cases from which the real sample is taken. It’s important to remember that the sampling frame is not a sample. Instead, it’s the operational description of the population that gives the sampling a place to start.

For example, in the Vidya Mandir case, if students in school and college are taken out of the sample, only students in professional classes (MBA, Computer Science, B.Ed., Home Science, and Biotechnology) are left. So, the sample frame cuts down on the total number of people and tells us who we want to study (i.e., only students of professional classes).

There are two reasons why sampling is done.

• Estimation of variables

• Putting a theory to the test Estimation of parameters: The main goal is to predict certain population parameters, such as how many office clerks worked overtime.

So, the study tries to pick a sample and figure out the important numbers (such as the average and the proportion). He can use this number as a guess to say something about how accurate it is in terms of standard errors and draw a conclusion about how many people live there in terms of probability.

Putting a theory to the test: The second goal of sampling could be to test a statistical theory about a group, such as the theory that at least 60% of households in the town of Kurukshetra have TVs.

The experts might choose a sample of homes and then figure out how many of those homes have TVs. Now, the problem is to figure out if the sample result is enough to say “no” to the theory or “yes” to it. To figure out how to solve this problem, the researcher needs to find a way to figure out how far off the sample result is from the hypothetical number.

Why we take samples,

Sarantakos has said that sampling is done for the following reasons:

• In many cases, the population may be so big and spread out that it may not be possible to cover everyone.

• It is very accurate because it only works with a small number of people. Most of us have had blood samples taken, sometimes from our fingers, sometimes from our arms, and sometimes from somewhere else on our bodies. The idea is that the blood is pretty much the same all over the body and that a sample is enough to figure out what the blood is like. Singleton and Straits have also said that looking at all cases will give a less true picture of the population than looking at a small sample.

Sampling is easier on investigators because it only needs a small part of the target group. It is also cheaper because it only needs a small number of people. A big population would mean hiring a lot of interviewers, which would raise the cost of the survey as a whole.

Many study projects, especially those that test quality control, require that the things being tested be thrown away. If the company that makes electric lights wants to know if each one meets a certain standard, there wouldn’t be any left after testing.

How to Pick a Sample:

The main idea behind sampling is that we try to learn about all the units (called the population) by looking at a small number of units (called the sample) and then applying what we learn from the sample to the whole population. With a cutter, we can take a small sample from the middle of a bag of wheat to tell if the wheat in the bag is good or not. But it’s not always true that a sample study gives us a good picture of the whole community.

If only a few people in a village agree that family planning is a good idea, that doesn’t mean that everyone in the village agrees. Opinions can be different based on religion, amount of education, age, wealth, and other things. From the study of a small number of people, the wrong conclusion or generalisation can be drawn because they are not a good representation of the whole community.

The study of a sample is needed because a study of a very big population would take a long time, a lot of interviewers, a lot of money, and the data collected by so many investigators might not be accurate. With a group, it is easier to plan an observation or study.

(Sarantakos):

The most important rules of sampling are:

• Sample units must be picked in a methodical and fair way.

• Sample units should be well-defined and easy to find.

• Each bit of a sample must be able to stand on its own.

• During the whole study, the same number of sample units should be used.

• The process for choosing winners should be based on good criteria and avoid mistakes, bias, and other kinds of misinformation.

The benefits of sampling:

Some of the benefits of sampling are shown by the reasons and rules we’ve talked about so far.

These things:

• It’s not possible to study a lot of people who are spread out over a big area. By taking samples, their number will go down.

• Time and money are saved.

• It saves destruction of units.

• It makes the data more accurate because you can keep track of the small number of people.

• It gets more people to answer.

It gets more help from those who answer.

It’s easy to keep an eye on a small number of interviewers in a sample, but it’s hard to keep an eye on a large number of interviewers in a study of the whole community. The researcher can stay out of sight.

Why sampling is important:

There are many reasons why selection is important when collecting statistics.

Only Possible, Fast, and Cheap Way: It’s quick and cheap and might be the only way to do it. In a factory, samples are used to check the quality of the goods. If the product is not good enough after being tested, it is either remade or thrown away. So, tasting is the only way to figure out how good something is. In the same way, instead of observing all things, it is faster and cheaper to pick a sample from the world and figure out what those things are like from that sample. It is a very useful tool for researchers and practitioners who want to keep certain characteristics of a community within certain limits.

Representativeness and Sample Size: The Problem of Sample Representatives When choosing a group, the main goal is to make sure it is as representative of the whole world as possible. Clearly, the size of a group does not always affect how representative it is.

So, if a small sample is chosen scientifically, it may be more accurate than a large sample chosen at random. Samples should be chosen so that every item in the population being studied has the same chance of being a good representation of the population as a whole.

A biassed sample is one that doesn’t show what the community is like as a whole.

Yule and Kendal point out that “the human being is a very poor tool for making a random selection.” When observers have the chance to make their own decisions or choices, bias is almost certain to creep in. Studies that use skewed sampling are inherently wrong and false. This is true of a number of studies in behavioural science that are based on surveys that were mailed out and only some of which were filled out and returned. The original mailing list of possible responders could, of course, be a good sample. But the surveys that were sent out may be very different from the ones that were actually sent back.

Sample Size Problem:

A scientific group is one that is both representative of the whole population and has enough cases to make sure the results are accurate. The question of whether a sample is enough is very complicated. According to Hagood and Price, the size of the sample can be determined by three things: the parameters that will be studied, the range of reliability that can be used in estimates, and a good idea of how far apart the studied characteristics are.

Different kinds of sampling:

Two types of sampling: probability sampling and non-probability sampling.

1. In probability sampling, every unit of the community has the same chance of being chosen for the sample. It is a good representation of the whole.

2. Non-probability sampling doesn’t claim to be representative because it doesn’t give every unit a chance to be chosen. The researcher is in charge of choosing the sample units.

Probability Sampling:

Probability sampling is still the best way to choose large, representative samples for business and social science studies. Black and Champion say that the following conditions must be met for probability sampling to work:

• There is a full list of all the things to study;

• The size of the universe must be known;

• The desired sample size must be stated; and

• Each element must have an equal chance of being chosen.

It means that they should use some kind of chance in at least one of their stages. Leabo divides probability samples into five groups: samples, random samples, sorted samples, and samples chosen at random.

Simple Random Sampling: Simple random samples are not used very often, but they are the base for other sampling methods. A simple random sample of n items is a sample taken from a community so that each possible combination of n units has the same chance or probability of being chosen.

Simple random sampling has the following benefits:

1. It saves time. Full coverage is more expensive than sampling, but the cost per unit is higher.

2. It saves time and money on labour. With sampling, fewer people are needed to gather, record, and handle the data. So, it saves a lot of work. 3. It saves time. Because of these benefits, sampling was used for the first time in the 1951 census of people.

This method saves a lot of time.

4. It improves accuracy. The overall amount of accuracy is higher when a sample is used. It makes it possible for the field to be better, with more checks for correctness, careful editing and analysis, and more detailed information.

Random sampling with a plan:

For these samples, the population is split into groups that are similar and a random sample is taken from each group. People can be put into groups based on what we know about them and how a certain feature group affects them. People can be put into groups based on what is known about them and how a certain trait affects the estimate that needs to be made.

The pros of stratified random sampling are as follows:

This process makes sure that each group and chance sample are properly represented. The way people were put into groups or classes was based on the type of problem being studied.

For example, if the problem is to figure out how much the average person makes in a certain area, occupational groups can be used as biases to divide the community. If it is done right, the stratified random sample is better than the sample random sample. In fact, the reliability of the data for a given sample size goes up as the range of all possible sample averages gets smaller. This means that a stratified random sample of the same size is more reliable than a simple random sample of the same size.

Non-probability sampling:

Probability sampling is hard to do and shouldn’t be used in many research situations, especially when there is no list of people to study (e.g., husbands who beat their wives, widows, people who own Maruti cars, people who use a certain type of detergent powder, alcoholics, students and teachers who skip class a lot, migrant workers, etc.). Non-probability sampling is the best way to do these kinds of studies. Non-probability sampling methods don’t use the rules of probability theory, don’t claim to be representative, and are usually used for qualitative exploratory analysis.

There is no randomness in these samples, so they can be called quota sampling, purposeful sampling, accidental sampling, or snowball sampling.

• Purposeful Sampling: This involves using your best judgement and making a concerted effort to get a sample that is representative of most places or groups.

Namjoshi’s work is a good example of what a purposive sample is. In this study, two types of people were asked to take part: 1. married men and women 2.Men and women who are not married. This method was used to choose both samples so that there would be enough people from higher and lower castes, different social groups, and both sexes. A group of 400 married men and women and a group of 400 single boys and girls were chosen as samples.

• Accidental sampling:– This is the weaker type of sampling because it uses the samples that are already out there. This type of sampling can be used if there are no other options.

• Snowball sampling: It refers to a set of procedures in which the first respondents are chosen by chance, and then more respondents are chosen based on the information they give. Referral is used with this method to find members of rare groups. For example, a company wants to sell a wood croquet set for serious adult players. Since the market for this product is small, researchers need to use this method to get the job done as cheaply as possible.

A theory is a guess about how variables are related to each other. It is a guess about what the research problem is or what the research results will be. Before starting the study, the researcher has a vague, even muddled idea of what the problem is. It might take the expert a long time to say what questions he was trying to answer. So, it is very important to have a good statement about the study problem.

• Theodor son and Theodor son: “A hypothesis is a tentative statement that suggests a link between certain facts.”

• Ker linger: “A hypothesis is a guess about the link between two or more variables.”

• Black and Champion have called it a “possible statement about something whose truth is often unknown.” This claim is meant to be tried in the real world to see if it is true or false. If the statement is not backed up by enough evidence, it is not a scientific rule.

Webster defines a hypothesis as “a tentative assumption made in order to find and test its logical or empirical consequences.” “Test” in this case means “either prove it wrong or prove it right.” Since statements in Hypothesis must be tested in the real world, the definition of hypothesis excludes all statements that are just opinions (e.g., getting older makes you sicker), value judgements (e.g., modern politicians are corrupt and have a vested interest to serve), or normative (e.g., everyone should take a morning walk). A normative statement is a statement about how things should be. It is not a statement of fact that can be proven right or wrong through research.

Some examples of theories are as follows:

• Group study improves performance in the upper level.

• Hostels use more.

• More crimes against women happen to young girls (15–30 years old) than to middle-aged women (30–40 years old).

• Men from the lower class commit more crimes than men from the middle class.

• The risk of suicide goes down when people spend less time alone.

• Women with less education have more trouble adjusting to marriage than women with more education.

• Most kids from broken homes grow up to be bad people.

• Unemployment lessens juvenile delinquency.

• People with more money have fewer children than people with less money.

Criteria for Building Hypotheses:

Hypothesis is never written out as a question. Bailey, Becker, Selltiz, and Sarantakos have all said that a theory must meet a number of criteria.

It should be able to be tested in the real world to see if it is right or wrong. It should be specific and clear.

• There shouldn’t be any contradictions in the claims in the hypothesis.

• It should list the factors that will be used to figure out the relationship.

• It should only talk about one thing.

You can write a theory in either a descriptive or a relational way. In the first, it explains what happened, while in the second, it shows how variables are related. A theory can also be in the form of a direction, a lack of direction, or the word “null.”

What hypotheses are:

The following must be true for a scientifically valid hypothesis:

• It must be true to the sociological facts that are important.

• It can’t go against what is known to be true in other science fields.

• It must take into account what other experts have found.

You can’t say whether a hypothesis is true or wrong. They can only be about the topic of the study or not. For example, poverty in a village can be caused by:

• Low growth of agriculture, which is caused by a lack of irrigation, sandy soil, unpredictable rain, and the use of traditional farming tools.

• Poverty is caused by a lack of infrastructure, like power, roads, and markets.

• Obstacles to rural growth include lack of resources (water, soil, minerals), lack of support (rain, irrigation, livestock), and problems with the social system (lack of credit, infrastructure, wasteful spending, and market problems).

The important hypotheses could be:

1. Rural poverty is linked to the availability and ease of getting loans.

2. Lack of infrastructure is the cause of rural poverty.

• People who are poor tend to spend a lot of money on social activities.

• Water, land, and mineral shortages are linked to rural poverty in a bad way.

Different kinds of hypotheses:

Hypotheses can be broken down into working hypotheses, study hypotheses, null hypotheses, statistical hypotheses, alternative hypotheses, and scientific hypotheses.

1. A working hypothesis is a researcher’s first guess about the topic of the research. It is used when there isn’t enough knowledge to make a hypothesis, or as a step towards making the final research hypothesis. Working theories are used to make the final research plan, put the research problem in the right context, and narrow down the research topic to a manageable size. In the area of business administration, for example, a researcher can come up with a working hypothesis like “promising a bonus makes a product sell more.” Later, after getting some preliminary data, he changes this idea and comes up with the study hypothesis that “promising a good bonus makes a product sell more.”

2. A scientific hypothesis has a statement that is based on or comes from enough theoretical and real-world facts.

3. An alternative hypothesis is a set of two hypotheses (research and null) that say the opposite of the null hypothesis. In statistical studies of null hypotheses, when Ho (the null hypothesis) is accepted, the alternative hypothesis is rejected, and when Ho is rejected, the alternative hypothesis is accepted.

4. A researcher’s study hypothesis is a statement about a social fact that doesn’t talk about its details. Researchers think it’s true and want to disprove it. For example, they think that Muslims have more children than Hindus or that upper-class students who live in dorms or rented rooms are more likely to use drugs. Theories can lead to research hypotheses or research hypotheses can lead to theories.

5. The study hypothesis is the opposite of the null hypothesis. It is a theory that there is no link. Null hypotheses are not real, but they are used to test other hypotheses in study.

6. According to Winter (1962), a statistical hypothesis is a statement or fact about statistical populations that a person wants to prove or disprove. Things are turned into numbers, and choices are made based on these numbers, like the difference in income between two groups: More money is in Group A than in Group B. The null hypothesis will be that Group A is not richer than Group B. Here, factors are turned into numbers that can be measured.

Goode and Hatt have identified three kinds of theories based on how abstract they are:

• That explains a claim in terms of common sense; that already has some common sense observations about it; or that tries to test claims that make sense. For instance, bad parents raise bad kids, managers who work hard always make money, and rich students drink more booze.

• Which are a little bit complicated, i.e., which describe a relationship that is a little bit complicated. • Religious polarisation leads to riots between different groups.

• Cities grow in rings that move outward from the centre (Burgess).

• Unstable economic conditions make it hard for a business to grow.

• Sutherland says that different relationships lead to crime.

• Living in poverty is linked to youth crime, according to Shaw.

• Healy and Bronner say that mental illnesses are the cause of bad behaviour.

• Which are very complex, meaning that they describe the relationship between two factors in more complicated terms. For example, high fertility is more common among people with low incomes, who are conservative, and who live in rural areas than among people with high incomes, who are modern, and who live in cities. In this case, “fertility” is the dependent variable, and “income, values, education, place of residence, etc.” are the independent variables. The other case is that Muslim women have more children than Hindu women. To test this theory, we have to keep a number of things the same. This is a vague way to deal with the issue.

Problems with coming up with hypotheses:

Goode and Hatt say that there are three main problems with making hypotheses:

1. Not being able to put the idea in the right way.

2. There isn’t a clear theoretical framework or the researcher doesn’t know about it. For example, a woman’s awareness of her rights relies on her personality and her environment (her schooling).

3. Not being able to use the theory framework in a logical way, such as with workers’ commitment, role skills, and learning roles.

4. You can tell if a theory is good or bad by how much information it gives about the thing being studied. Take the following theory, which is given in three different ways:

• X is linked to Y.

• X depends on Y.

Things that make a hypothesis useful:

Goode and Hatt have said that a good theory has the following traits:

• The main idea must be clear. This means that ideas should be explained in clear terms. These ideas should be put into action. Most people should agree with these. These should be easy to share. The idea behind the statement “as institutionalisation goes up, production goes down” is not easy to explain.

• It should be based on real-world examples. This means that the factors should be able to be tested in the real world. They shouldn’t just be moral judgements. For example, capitalists take advantage of their workers, officers take advantage of their subordinates, young people are more bold in their ideas, and good management leads to good relationships in a business. These ideas can’t be thought of as useful ideas.

• It should be clear, like “Vertical mobility in industries is decreasing” or “Exploitation leads to agitation.”

• It should be linked to techniques that can be used. This means that not only should the researcher know about the techniques, but they should also be able to be used. Take the statement, “Changes in infrastructure (means of production and relationships of production) lead to changes in social structure (family, religion, etc.).” With the tools we have, we can’t test this kind of theory.

• It should fit into a body of knowledge.

Where Hypotheses Come From:

1. The cultural ideals of a society. For example, American culture values individualism, mobility, competition, and equality, while Indian culture values tradition, collectivism, karma, and not being attached to anything. So, Indian traditional values let us come up with and test the following ideas:

• The number of Indian families who live together has gone down, but they still work together.

• Divorce is the last thing a woman will do to end her marriage.

• The way Indians vote depends on their caste.

• An Indian family usually includes not only first and second cousins, but also third cousins and even distant cousins.

2. Past study: Hypotheses are often based on research that has already been done. For example, a researcher looking into student unrest might use the results of another study that say “students who have been in college or university for two or three years are more interested in student problems on campus than freshmen” or “students with high ability and high social status are less likely to take part in student agitations than students with low ability and low social status.” Such theories could be used to either confirm the results of previous studies or change the ideas that the supposed correlation does not exist.

3. Folk wisdom: Sometimes, researchers get an idea for a hypothesis from a widely held belief, such as that a person’s caste affects how they act, or that geniuses have unhappy marriages, or that married women without children are less happy, or that young, uneducated married girls are more likely to be exploited in joint families, or that being an only child makes it harder for a child to develop certain personality traits, and so on.

Discussions and conversations: People’s random observations and thoughts about their own lives shed light on events and problems.

5. Personal experiences: Researchers often see proof of certain patterns of behaviour in their everyday lives. Intuition: Sometimes, investigators have a gut feeling that something is connected to something else. The investigator makes a guess about a link between the two things and then does a study to see if his or her guess is right. For example, someone who has lived in a hotel for a few years might think that “lack of control leads to bad behaviour.” So, he or she begins to study the subculture of hostels.

What hypotheses do or how important they are:

Sarantakos has pointed out that theories do the following three things:

1. To help organise and run social research. 2. To give a temporary answer to the research question. 3. To make statistical analysis of variables easier in the context of hypothesis testing.

You can also say the following about how important theories are:

1. Hypotheses are important for scientific study and inquiry because they come from theory or lead to theory.

2. The facts (in theories) have a chance to show that the likely truth is true or that it is not true.

Hypotheses are used to learn more because they are not based on people’s ideals or opinions.

4. Hypotheses help social scientists come up with theories that could explain and predict what will happen.

5. Hypotheses describe what is going on. The fact that the theory was tested tells us something about the thing it is about. In a nutshell, hypotheses are mostly used to test theories, suggest new theories, and explain social events.

The secondary functions are to help make social policy, such as for rural communities, prisons, slums in cities, educational institutions, and solutions to different kinds of social problems; to help disprove some “common sense” ideas, such as the idea that men are smarter than women; and to show that systems and structures need to change by giving new information.

Criticisms of Hypotheses:

• Some experts have said that every study needs a hypothesis. The development of a theory can help not only exploratory and explanatory research, but also descriptive research. But this view has been criticised by other experts. They say that hypotheses do not help the study process in any way. On the contrary, they may affect how the experts collect and analyse data. They might limit what they do and how they do it. They might even be able to predict how the research study will turn out.

• Qualitative researchers say that theories are important tools in social research, but they shouldn’t come before the research. Instead, they should come out of the research.

Even though these two points are at odds with each other, many researchers use hypotheses, whether they say so or not. The biggest benefit is that they not only help you set goals for your study, but they also help you focus on the most important parts of your topic by letting you skip over the less important ones.

Reliability is how consistent your measurements are, or how much a tool measures the same way every time it is used in the same way with the same people. In short, it’s how often you can measure the same thing. If a person gets the same score on the same test twice, we say that the measure is reliable. It’s important to remember that reliability is not tested, it’s estimated.

Most of the time, there are two ways to figure out how reliable something is: Test/Retest and Internal Consistency.

Test/retest: Test/retest is the more

safe way to figure out how reliable something is. The idea behind test/retest is that your score on test 1 should be the same as your score on test 2. The three most important parts of this method are:

• Use your measuring tool on each subject twice at different times;

• Figure out the relationship between the two readings; and

• Assume that the underlying condition or trait you are trying to measure hasn’t changed between test 1 and test 2.

2.Internal Consistency: Internal consistency measures reliability by grouping questions in a questionnaire that measure the same idea. For example, you could write two sets of three questions that measure the same thing, like class involvement, and then compare the answers to see if your instrument is accurately measuring that thing.

The main difference between test/retest and internal consistency measures of reliability is that test/retest involves giving the measurement tool twice, while the internal consistency method only requires giving the measurement tool once.

Validity is how strong our findings, inferences, or statements are. In a more formal way, Cook and Campbell (1979) say that it is the “best available approximation to the truth or falsity of a given inference, proposition, or conclusion.” To put it simply, were we right? Let’s look at a simple case. Say we are looking into how strict attendance rules affect how many people show up to class. In our case, we saw that more people did come to class after the strategy was put in place. Each type of validity would show a different part of the link between our treatment (a strict policy on attendance) and the result we saw (more people in class).

Types of Validity; In social study, there are four main types of validity:

1. Conclusion truth asks if there is a link between what was done and what was seen. Or, in our case, is there a link between the policy on attendance and the fact that more people showed up?

2. Internal validity asks if there is a cause-and-effect link between the programme and the results we saw. For instance, did the attendance rules make more people come to class?

3.Construct validity is the most difficult for me to understand. It asks if there is a connection between how I operationalized my concepts in this study and the real causal relationship I’m trying to study. Or, in our case, did our treatment (the policy on attendance) match the concept of attendance? Did our measured outcome (more people in class) match the concept of participation? Overall, we are trying to apply how we think about treatment and results to a wider range of similar ideas.

4. External validity means that the results of our work can be used in other places. In our case, are our results something that could be used in other classrooms?

Marriage between Value and Trustworthiness

• The main thing that makes the difference between dependability and validity is how you define them. Reliability is a way to figure out how consistent your measurements are, or how much an instrument measures the same way every time it is used in the same way with the same people. Validity, on the other hand, is about how well you measure what you’re meant to measure, or, in other words, how accurate your measurement is. I think validity is more important than reliability because if an instrument doesn’t measure what it’s meant to measure accurately, there’s no point in using it, even if it measures the same thing every time (reliably).

So, what is the link between truth and reliability? These two things don’t always go together. At best, we have a way to measure that is both accurate and valid. It gives the same results every time, and it’s a good representation of what we want to stand for.It is possible for a measure to be very reliable but not very true. This means that it consistently gives wrong information or misses the mark. It is also possible for one to be inconsistent and not on goal, with low reliability and validity.

Lastly, a measure can’t be both unreliable and accurate. If your measure changes all over the place, you can’t really find out what you want or what you’re interested in.

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ReviseSociology

A level sociology revision – education, families, research methods, crime and deviance and more!

Experiments in Sociology – Revision Notes

Table of Contents

Last Updated on September 6, 2021 by

Definitions, key features and the theoretical, practical and ethical strengths and limitations of laboratory and field experiments applied to sociology (and psychology). Also covers key terms related to experiments.

post has been written to help students revising for the research methods aspect of their second year A-level exams.

Experiments – The Basics: Definitions/ Key Features

• Experiments aim to measure the effect which one or more independent variables have on a dependent variable.
• The aim is to isolate and measure as precisely as possible the exact effect independent variables have on dependent variables.
• Experiments typically aim to test a ‘hypothesis’ – a prediction about how one variable will effect another.
• Laboratory Experiments take place in an artificial, controlled environment such as a laboratory.
• Field Experiments – take place in a real world context such as a school or a hospital.

Advantages of Laboratory Experiments

• Theoretical – The controlled conditions of laboratory experiments allow researchers to isolate variables: you can precisely measure the exact effect of one thing on another.
• Theoretical – You can establish cause and effect relationships.
• Theoretical – You can collect ‘objective’ knowledge – about how facts ‘out there’ affect individuals.
• Theoretical – Good Reliability because it is easy to replicate the exact same conditions.
• Theoretical – Good Reliability because of the high level of detachment between the researcher and the respondent.
• Practical – Easy to attract funding because of the prestige of science.
• Practical – Take place in one setting so researchers can conduct research like any other day-job – no need to chase respondents.
• Ethical – Most laboratory experiments seek to gain informed consent, often a requirement to get funding.
• Ethical – Legality – lab experiments rarely ask participants to do anything illegal.
• Ethical – Findings benefit society – both Milgram and Zimbardo would claim the shocking findings of their research outweigh the harms done to respondents.

Disadvantages of Laboratory Experiments

• Theoretical – They are reductionist: human behaviour cannot be explained through simple cause and effect relationships (people are not ‘puppets’).
• Theoretical – Laboratory experiments lack external validity – the artificial environment is so far removed from real-life that the results tell us very little about how respondents would actually act in real life.
• Theoretical – The Hawthorne Effect may further reduce validity – respondents may act differently just because they know they are part of an experiment.
• Theoretical – They are small scale and thus unrepresentative.
• Practical – It is impractical to observe large scale social processes in a laboratory – you cannot get whole towns, let alone countries of people into the small scale setting of a laboratory.
• Practical – Time – Small samples mean you will need to conduct consecutive experiments on small groups if you want large samples, which will take time
• Ethical – Deception and lack of informed consent – it is often necessary to deceive subjects as to the true nature of the experiment so that they do not act differently. Links to the Hawthorne Effect.
• Ethical – Some specific experiments have resulted in harm to respondents – in the Milgram experiment for example.
• Ethical – Interpretivists may be uncomfortable with the unequal relationships between researcher and respondent – the researcher takes on the role of the expert, who decides what is worth knowing in advance of the experiment.

Advantages of Field Experiments over Laboratory Experiments

• Theoretical – They generally have better validity than lab experiments because they take place in real life settings
• Theoretical – Better external validity – because they take place in normally occurring, real-world social settings.
• Practical – Larger scale settings – you can do field experiments in schools or workplaces, so you can observe large scale social processes, which isn’t possible with laboratory experiments.
• Practical – a researcher can ‘set up’ a field experiment and let it run for a year, and then come back later.

The relative disadvantages of Field Experiments

• Theoretical – It is not possible to control variables as closely as with laboratory experiments – because it’s impossible to observe respondents 100% of the time.
• Theoretical – Reliability is weaker – because it’s more difficult to replicate the exact context of the research again.
• Theoretical – The Hawthorne Effect (or Experimental Effect) may reduce the validity of results.
• Practical Problems – access is likely to be more of a problem with lab experiments. Schools and workplaces might be reluctant to allow researchers in.
• Ethical Problems – As with lab experiments – it is often possible to not inform people that an experiment is taking place in order for them to act naturally, so the issues of deception and lack of informed consent apply here too, as does the issue of harm.

Experiments – Key Terms Summary

Hypothesis – a theory or explanation made on the basis of limited evidence as a starting point for further investigation. A hypothesis will typically take the form of a testable statement about the effect which one or more independent variables will have on the dependent variable.

Dependent Variable – this is the object of the study in the experiment, the variable which will (possibly) be effected by the independent variables.

Independent variables – The variables which are varied in an experiment – the factors which the experimenter changes in order to measure the effect they have on the dependent variable.

Extraneous variables – Variables which are not of interest to the researcher but which may interfere with the results of an experiment

Experimental group – The group under study in the investigation.

Control group – The group which is similar to the study group who are held constant. Following the experiment the experimental group can be compared to the control group to measure the extent of the impact (if any) of the independent variables.

You should also know about natural experiments/ the comparative method –involves comparing two or more societies or groups which are similar in some respects but varied in others, and looking for correlations.  

Signposting

This post has been written to help students revising for the research methods aspect of their second year A-level exams.

These are the more in-depth posts on experiments

Experiments in sociology – an introduction

Laboratory experiments in sociology

Field experiments in sociology

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1.1 What Is Sociology?

Learning objectives.

By the end of this section, you should be able to:

• Explain concepts central to sociology.
• Describe how different sociological perspectives have developed.

What Are Society and Culture?

Sociology is the scientific and systematic study of groups and group interactions, societies and social interactions, from small and personal groups to very large groups. A group of people who live in a defined geographic area, who interact with one another, and who share a common culture is what sociologists call a society .

Sociologists study all aspects and levels of society. Sociologists working from the micro-level study small groups and individual interactions, while those using macro-level analysis look at trends among and between large groups and societies. For example, a micro-level study might look at the accepted rules of conversation in various groups such as among teenagers or business professionals. In contrast, a macro-level analysis might research the ways that language use has changed over time or in social media outlets.

The term culture refers to the group’s shared practices, values, and beliefs. Culture encompasses a group’s way of life, from routine, everyday interactions to the most important parts of group members’ lives. It includes everything produced by a society, including all the social rules.

Sociologists often study culture using the sociological imagination , which pioneer sociologist C. Wright Mills described as an awareness of the relationship between a person’s behavior and experience and the wider culture that shaped the person’s choices and perceptions. It’s a way of seeing our own and other people’s behavior in relationship to history and social structure (1959). One illustration of this is a person’s decision to marry. In the United States, this choice is heavily influenced by individual feelings. However, the social acceptability of marriage relative to the person’s circumstances also plays a part.

Remember, though, that culture is a product of the people in a society. Sociologists take care not to treat the concept of “culture” as though it were alive and real. The error of treating an abstract concept as though it has a real, material existence is known as reification (Sahn, 2013).

Studying Patterns: How Sociologists View Society

All sociologists are interested in the experiences of individuals and how those experiences are shaped by interactions with social groups and society. To a sociologist, the personal decisions an individual makes do not exist in a vacuum. Cultural patterns , social forces and influences put pressure on people to select one choice over another. Sociologists try to identify these general patterns by examining the behavior of large groups of people living in the same society and experiencing the same societal pressures.

Consider the changes in U.S. families. The “typical” family in past decades consisted of married parents living in a home with their unmarried children. Today, the percent of unmarried couples, same-sex couples, single-parent and single-adult households is increasing, as well as is the number of expanded households, in which extended family members such as grandparents, cousins, or adult children live together in the family home. While 15 million mothers still make up the majority of single parents, 3.5 million fathers are also raising their children alone (U.S. Census Bureau, 2020). Increasingly, single people and cohabitating couples are choosing to raise children outside of marriage through surrogates or adoption.

Some sociologists study social facts —the laws, morals, values, religious beliefs, customs, fashions, rituals, and cultural rules that govern social life—that may contribute to these changes in the family. Do people in the United States view marriage and family differently over the years? Do they view them differently than Peruvians? Do employment and economic conditions play a role in families? Other sociologists are studying the consequences of these new patterns, such as the ways children influence and are influenced by them and/or the changing needs for education, housing, and healthcare.

Sociologists identify and study patterns related to all kinds of contemporary social issues. The “Stop and Frisk” policy, the emergence of new political factions, how Twitter influences everyday communication—these are all examples of topics that sociologists might explore.

Studying Part and Whole: How Sociologists View Social Structures

A key component of the sociological perspective is the idea that the individual and society are inseparable. It is impossible to study one without the other. German sociologist Norbert Elias called the process of simultaneously analyzing the behavior of individuals and the society that shapes that behavior figuration .

Consider religion. While people experience religion in a distinctly individual manner, religion exists in a larger social context as a social institution . For instance, an individual’s religious practice may be influenced by what government dictates, holidays, teachers, places of worship, rituals, and so on. These influences underscore the important relationship between individual practices of religion and social pressures that influence that religious experience (Elias, 1978). In simpler terms, figuration means that as one analyzes the social institutions in a society, the individuals using that institution in any fashion need to be ‘figured’ in to the analysis.

Sociology in the Real World

Individual-society connections.

When sociologist Nathan Kierns spoke to his friend Ashley (a pseudonym) about the move she and her partner had made from an urban center to a small Midwestern town, he was curious about how the social pressures placed on a lesbian couple differed from one community to the other. Ashley said that in the city they had been accustomed to getting looks and hearing comments when she and her partner walked hand in hand. Otherwise, she felt that they were at least being tolerated. There had been little to no outright discrimination.

Things changed when they moved to the small town for her partner’s job. For the first time, Ashley found herself experiencing direct discrimination because of her sexual orientation. Some of it was particularly hurtful. Landlords would not rent to them. Ashley, who is a highly trained professional, had a great deal of difficulty finding a new job.

When Nathan asked Ashley if she and her partner became discouraged or bitter about this new situation, Ashley said that rather than letting it get to them, they decided to do something about it. Ashley approached groups at a local college and several churches in the area. Together they decided to form the town's first Gay-Straight Alliance.

The alliance has worked successfully to educate their community about same-sex couples. It also worked to raise awareness about the kinds of discrimination that Ashley and her partner experienced in the town and how those could be eliminated. The alliance has become a strong advocacy group, and it is working to attain equal rights for lesbian, gay, bisexual, and transgender, or LGBTQ individuals.

Kierns observed that this is an excellent example of how negative social forces can result in a positive response from individuals to bring about social change (Kierns, 2011).

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• Authors: Tonja R. Conerly, Kathleen Holmes, Asha Lal Tamang
• Publisher/website: OpenStax
• Book title: Introduction to Sociology 3e
• Publication date: Jun 3, 2021
• Location: Houston, Texas
• Book URL: https://openstax.org/books/introduction-sociology-3e/pages/1-introduction
• Section URL: https://openstax.org/books/introduction-sociology-3e/pages/1-1-what-is-sociology

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