hypothesis of social research

Theory in Social Research

• First Online: 27 October 2022

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• Mumtaz Ali 4 ,
• Maya Khemlani David 5 &
• Kuang Ching Hei 5  

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In this chapter, the importance and link between social research and theory are discussed. Social research is taken as the sociological understanding of connections—connections between action, experience, and change—and it is the major vehicle for realizing these connections. The debate on using theory in any scope of social research is being deliberated by various scholars with many emphasizing the merits of using theory in social research. They argue that an appropriate theory clarifies the findings a researcher has uncovered in the study. Without a theory, the researcher could face difficulties in streamlining the study or the researcher may overlook particular phenomena or events from within the study. Thus, the researcher would be unable to relate the variables in the study. A theorist always tries to view things from his/her perspective. Upon reflection, the theorist may develop a refined framework which then becomes the intensive framework, hereby, called a theory. This phenomenon may not necessarily be agreed upon by every social scientist as can be illustrated by cases where, after using a theory, researchers have modified such a theory to suit their outcomes. The theory used in social research supports and facilitates the researcher to raise fundamental questions and facts which could serve as the common core or body of knowledge. From the basis of given facts and explanations, it can be claimed that the theory used in social research has a pivotal role to align the study. In social research, a researcher should make the matter of selecting a theory seriously as a good theory produces a better piece of research work. This chapter elaborates on the various aspects of using theory in social research. Several diagrams are used to make explanations clear.

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Ali, M., David, M.K., Hei, K.C. (2022). Theory in Social Research. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_4

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Chapter 3: Developing a Research Question

3.4 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 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 Chapter5.2in Principles of Sociological Inquiry , which was adapted by the Saylor Academy without attribution to the original authors or publisher, as requested by the licensor. © CreativeCommonsAttribution-NonCommercial-ShareAlike 3.0 License .

Research Methods for the Social Sciences: An Introduction Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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2.1C: Formulating the Hypothesis

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A hypothesis is a potential answer to your research question; the research process helps you determine if your hypothesis is true.

Learning Objectives

• Explain how hypotheses are used in sociological research and the difference between dependent and independent variables
• Hypotheses are testable explanations of a problem, phenomenon, or observation.
• Both quantitative and qualitative research involve formulating a hypothesis to address the research problem.
• Hypotheses that suggest a causal relationship involve at least one independent variable and at least one dependent variable; in other words, one variable which is presumed to affect the other.
• An independent variable is one whose value is manipulated by the researcher or experimenter.
• A dependent variable is a variable whose values are presumed to change as a result of changes in the independent variable.
• dependent variable : In an equation, the variable whose value depends on one or more variables in the equation.
• independent variable : In an equation, any variable whose value is not dependent on any other in the equation.
• hypothesis : Used loosely, a tentative conjecture explaining an observation, phenomenon, or scientific problem that can be tested by further observation, investigation, or experimentation.

A hypothesis is an assumption or suggested explanation about how two or more variables are related. It is a crucial step in the scientific method and, therefore, a vital aspect of all scientific research. There are no definitive guidelines for the production of new hypotheses. The history of science is filled with stories of scientists claiming a flash of inspiration, or a hunch, which then motivated them to look for evidence to support or refute the idea.

While there is no single way to develop a hypothesis, a useful hypothesis will use deductive reasoning to make predictions that can be experimentally assessed. If results contradict the predictions, then the hypothesis under examination is incorrect or incomplete and must be revised or abandoned. If results confirm the predictions, then the hypothesis might be correct but is still subject to further testing.

Both quantitative and qualitative research involve formulating a hypothesis to address the research problem. A hypothesis will generally provide a causal explanation or propose some association between two variables. Variables are measurable phenomena whose values can change under different conditions. For example, if the hypothesis is a causal explanation, it will involve at least one dependent variable and one independent variable. In research, independent variables are the cause of the change. The dependent variable is the effect, or thing that is changed. In other words, the value of a dependent variable depends on the value of the independent variable. Of course, this assumes that there is an actual relationship between the two variables. If there is no relationship, then the value of the dependent variable does not depend on the value of the independent variable.

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4 Theories in scientific research

As we know from previous chapters, science is knowledge represented as a collection of ‘theories’ derived using the scientific method. In this chapter, we will examine what a theory is, why we need theories in research, the building blocks of a theory, how to evaluate theories, how can we apply theories in research, and also present illustrative examples of five theories frequently used in social science research.

Theories are explanations of a natural or social behaviour, event, or phenomenon. More formally, a scientific theory is a system of constructs (concepts) and propositions (relationships between those constructs) that collectively presents a logical, systematic, and coherent explanation of a phenomenon of interest within some assumptions and boundary conditions (Bacharach 1989). [1]

Theories should explain why things happen, rather than just describe or predict. Note that it is possible to predict events or behaviours using a set of predictors, without necessarily explaining why such events are taking place. For instance, market analysts predict fluctuations in the stock market based on market announcements, earnings reports of major companies, and new data from the Federal Reserve and other agencies, based on previously observed correlations . Prediction requires only correlations. In contrast, explanations require causations , or understanding of cause-effect relationships. Establishing causation requires three conditions: one, correlations between two constructs, two, temporal precedence (the cause must precede the effect in time), and three, rejection of alternative hypotheses (through testing). Scientific theories are different from theological, philosophical, or other explanations in that scientific theories can be empirically tested using scientific methods.

Explanations can be idiographic or nomothetic. Idiographic explanations are those that explain a single situation or event in idiosyncratic detail. For example, you did poorly on an exam because: you forgot that you had an exam on that day, you arrived late to the exam due to a traffic jam, you panicked midway through the exam, you had to work late the previous evening and could not study for the exam, or even your dog ate your textbook. The explanations may be detailed, accurate, and valid, but they may not apply to other similar situations, even involving the same person, and are hence not generalisable. In contrast, nomothetic explanations seek to explain a class of situations or events rather than a specific situation or event. For example, students who do poorly in exams do so because they did not spend adequate time preparing for exams or because they suffer from nervousness, attention-deficit, or some other medical disorder. Because nomothetic explanations are designed to be generalisable across situations, events, or people, they tend to be less precise, less complete, and less detailed. However, they explain economically, using only a few explanatory variables. Because theories are also intended to serve as generalised explanations for patterns of events, behaviours, or phenomena, theoretical explanations are generally nomothetic in nature.

While understanding theories, it is also important to understand what theories are not. A theory is not data, facts, typologies, taxonomies, or empirical findings. A collection of facts is not a theory, just as a pile of stones is not a house. Likewise, a collection of constructs (e.g., a typology of constructs) is not a theory, because theories must go well beyond constructs to include propositions, explanations, and boundary conditions. Data, facts, and findings operate at the empirical or observational level, while theories operate at a conceptual level and are based on logic rather than observations.

There are many benefits to using theories in research. First, theories provide the underlying logic for the occurrence of natural or social phenomena by explaining the key drivers and outcomes of the target phenomenon, and the underlying processes responsible for driving that phenomenon. Second, they aid in sense-making by helping us synthesise prior empirical findings within a theoretical framework and reconcile contradictory findings by discovering contingent factors influencing the relationship between two constructs in different studies. Third, theories provide guidance for future research by helping identify constructs and relationships that are worthy of further research. Fourth, theories can contribute to cumulative knowledge building by bridging gaps between other theories and by causing existing theories to be re-evaluated in a new light.

However, theories can also have their own share of limitations. As simplified explanations of reality, theories may not always provide adequate explanations of the phenomenon of interest based on a limited set of constructs and relationships. Theories are designed to be simple and parsimonious explanations, while reality may be significantly more complex. Furthermore, theories may impose blinders or limit researchers’ ‘range of vision’, causing them to miss out on important concepts that are not defined by the theory.

Building blocks of a theory

David Whetten (1989) [2] suggests that there are four building blocks of a theory: constructs, propositions, logic, and boundary conditions/assumptions. Constructs capture the ‘what’ of theories (i.e., what concepts are important for explaining a phenomenon?), propositions capture the ‘how’ (i.e., how are these concepts related to each other?), logic represents the ‘why’ (i.e., why are these concepts related?), and boundary conditions/assumptions examines the ‘who, when, and where’ (i.e., under what circumstances will these concepts and relationships work?). Though constructs and propositions were previously discussed in Chapter 2, we describe them again here for the sake of completeness.

Constructs are abstract concepts specified at a high level of abstraction that are chosen specifically to explain the phenomenon of interest. Recall from Chapter 2 that constructs may be unidimensional (i.e., embody a single concept), such as weight or age, or multi-dimensional (i.e., embody multiple underlying concepts), such as personality or culture. While some constructs, such as age, education, and firm size, are easy to understand, others, such as creativity, prejudice, and organisational agility, may be more complex and abstruse, and still others such as trust, attitude, and learning may represent temporal tendencies rather than steady states. Nevertheless, all constructs must have clear and unambiguous operational definitions that should specify exactly how the construct will be measured and at what level of analysis (individual, group, organisational, etc.). Measurable representations of abstract constructs are called variables . For instance, IQ score is a variable that is purported to measure an abstract construct called ‘intelligence’. As noted earlier, scientific research proceeds along two planes: a theoretical plane and an empirical plane. Constructs are conceptualised at the theoretical plane, while variables are operationalised and measured at the empirical (observational) plane. Furthermore, variables may be independent, dependent, mediating, or moderating, as discussed in Chapter 2. The distinction between constructs (conceptualised at the theoretical level) and variables (measured at the empirical level) is shown in Figure 4.1.

Propositions are associations postulated between constructs based on deductive logic. Propositions are stated in declarative form and should ideally indicate a cause-effect relationship (e.g., if X occurs, then Y will follow). Note that propositions may be conjectural but must be testable, and should be rejected if they are not supported by empirical observations. However, like constructs, propositions are stated at the theoretical level, and they can only be tested by examining the corresponding relationship between measurable variables of those constructs. The empirical formulation of propositions, stated as relationships between variables, are called hypotheses . The distinction between propositions (formulated at the theoretical level) and hypotheses (tested at the empirical level) is depicted in Figure 4.1.

The third building block of a theory is the logic that provides the basis for justifying the propositions as postulated. Logic acts like a ‘glue’ that connects the theoretical constructs and provides meaning and relevance to the relationships between these constructs. Logic also represents the ‘explanation’ that lies at the core of a theory. Without logic, propositions will be ad hoc, arbitrary, and meaningless, and cannot be tied into the cohesive ‘system of propositions’ that is the heart of any theory.

Finally, all theories are constrained by assumptions about values, time, and space, and boundary conditions that govern where the theory can be applied and where it cannot be applied. For example, many economic theories assume that human beings are rational (or boundedly rational) and employ utility maximisation based on cost and benefit expectations as a way of understand human behaviour. In contrast, political science theories assume that people are more political than rational, and try to position themselves in their professional or personal environment in a way that maximises their power and control over others. Given the nature of their underlying assumptions, economic and political theories are not directly comparable, and researchers should not use economic theories if their objective is to understand the power structure or its evolution in an organisation. Likewise, theories may have implicit cultural assumptions (e.g., whether they apply to individualistic or collective cultures), temporal assumptions (e.g., whether they apply to early stages or later stages of human behaviour), and spatial assumptions (e.g., whether they apply to certain localities but not to others). If a theory is to be properly used or tested, all of the implicit assumptions that form the boundaries of that theory must be properly understood. Unfortunately, theorists rarely state their implicit assumptions clearly, which leads to frequent misapplications of theories to problem situations in research.

Attributes of a good theory

Theories are simplified and often partial explanations of complex social reality. As such, there can be good explanations or poor explanations, and consequently, there can be good theories or poor theories. How can we evaluate the ‘goodness’ of a given theory? Different criteria have been proposed by different researchers, the more important of which are listed below:

Logical consistency: Are the theoretical constructs, propositions, boundary conditions, and assumptions logically consistent with each other? If some of these ‘building blocks’ of a theory are inconsistent with each other (e.g., a theory assumes rationality, but some constructs represent non-rational concepts), then the theory is a poor theory.

Explanatory power: How much does a given theory explain (or predict) reality? Good theories obviously explain the target phenomenon better than rival theories, as often measured by variance explained (R-squared) value in regression equations.

Falsifiability: British philosopher Karl Popper stated in the 1940s that for theories to be valid, they must be falsifiable. Falsifiability ensures that the theory is potentially disprovable, if empirical data does not match with theoretical propositions, which allows for their empirical testing by researchers. In other words, theories cannot be theories unless they can be empirically testable. Tautological statements, such as ‘a day with high temperatures is a hot day’ are not empirically testable because a hot day is defined (and measured) as a day with high temperatures, and hence, such statements cannot be viewed as a theoretical proposition. Falsifiability requires the presence of rival explanations, it ensures that the constructs are adequately measurable, and so forth. However, note that saying that a theory is falsifiable is not the same as saying that a theory should be falsified. If a theory is indeed falsified based on empirical evidence, then it was probably a poor theory to begin with.

Parsimony: Parsimony examines how much of a phenomenon is explained with how few variables. The concept is attributed to fourteenth century English logician Father William of Ockham (and hence called ‘Ockham’s razor’ or ‘Occam’s razor’), which states that among competing explanations that sufficiently explain the observed evidence, the simplest theory (i.e., one that uses the smallest number of variables or makes the fewest assumptions) is the best. Explanation of a complex social phenomenon can always be increased by adding more and more constructs. However, such an approach defeats the purpose of having a theory, which is intended to be a ‘simplified’ and generalisable explanation of reality. Parsimony relates to the degrees of freedom in a given theory. Parsimonious theories have higher degrees of freedom, which allow them to be more easily generalised to other contexts, settings, and populations.

Approaches to theorising

How do researchers build theories? Steinfeld and Fulk (1990) [3] recommend four such approaches. The first approach is to build theories inductively based on observed patterns of events or behaviours. Such an approach is often called ‘grounded theory building’, because the theory is grounded in empirical observations. This technique is heavily dependent on the observational and interpretive abilities of the researcher, and the resulting theory may be subjective and non-confirmable. Furthermore, observing certain patterns of events will not necessarily make a theory, unless the researcher is able to provide consistent explanations for the observed patterns. We will discuss the grounded theory approach in a later chapter on qualitative research.

The second approach to theory building is to conduct a bottom-up conceptual analysis to identify different sets of predictors relevant to the phenomenon of interest using a predefined framework. One such framework may be a simple input-process-output framework, where the researcher may look for different categories of inputs, such as individual, organisational, and/or technological factors potentially related to the phenomenon of interest (the output), and describe the underlying processes that link these factors to the target phenomenon. This is also an inductive approach that relies heavily on the inductive abilities of the researcher, and interpretation may be biased by researcher’s prior knowledge of the phenomenon being studied.

The third approach to theorising is to extend or modify existing theories to explain a new context, such as by extending theories of individual learning to explain organisational learning. While making such an extension, certain concepts, propositions, and/or boundary conditions of the old theory may be retained and others modified to fit the new context. This deductive approach leverages the rich inventory of social science theories developed by prior theoreticians, and is an efficient way of building new theories by expanding on existing ones.

The fourth approach is to apply existing theories in entirely new contexts by drawing upon the structural similarities between the two contexts. This approach relies on reasoning by analogy, and is probably the most creative way of theorising using a deductive approach. For instance, Markus (1987) [4] used analogic similarities between a nuclear explosion and uncontrolled growth of networks or network-based businesses to propose a critical mass theory of network growth. Just as a nuclear explosion requires a critical mass of radioactive material to sustain a nuclear explosion, Markus suggested that a network requires a critical mass of users to sustain its growth, and without such critical mass, users may leave the network, causing an eventual demise of the network.

Examples of social science theories

In this section, we present brief overviews of a few illustrative theories from different social science disciplines. These theories explain different types of social behaviors, using a set of constructs, propositions, boundary conditions, assumptions, and underlying logic. Note that the following represents just a simplistic introduction to these theories. Readers are advised to consult the original sources of these theories for more details and insights on each theory.

Agency theory. Agency theory (also called principal-agent theory), a classic theory in the organisational economics literature, was originally proposed by Ross (1973) [5] to explain two-party relationships—such as those between an employer and its employees, between organisational executives and shareholders, and between buyers and sellers—whose goals are not congruent with each other. The goal of agency theory is to specify optimal contracts and the conditions under which such contracts may help minimise the effect of goal incongruence. The core assumptions of this theory are that human beings are self-interested individuals, boundedly rational, and risk-averse, and the theory can be applied at the individual or organisational level.

The two parties in this theory are the principal and the agent—the principal employs the agent to perform certain tasks on its behalf. While the principal’s goal is quick and effective completion of the assigned task, the agent’s goal may be working at its own pace, avoiding risks, and seeking self-interest—such as personal pay—over corporate interests, hence, the goal incongruence. Compounding the nature of the problem may be information asymmetry problems caused by the principal’s inability to adequately observe the agent’s behaviour or accurately evaluate the agent’s skill sets. Such asymmetry may lead to agency problems where the agent may not put forth the effort needed to get the task done (the moral hazard problem) or may misrepresent its expertise or skills to get the job but not perform as expected (the adverse selection problem). Typical contracts that are behaviour-based, such as a monthly salary, cannot overcome these problems. Hence, agency theory recommends using outcome-based contracts, such as commissions or a fee payable upon task completion, or mixed contracts that combine behaviour-based and outcome-based incentives. An employee stock option plan is an example of an outcome-based contract, while employee pay is a behaviour-based contract. Agency theory also recommends tools that principals may employ to improve the efficacy of behaviour-based contracts, such as investing in monitoring mechanisms—e.g. hiring supervisors—to counter the information asymmetry caused by moral hazard, designing renewable contracts contingent on the agent’s performance (performance assessment makes the contract partially outcome-based), or by improving the structure of the assigned task to make it more programmable and therefore more observable.

Theory of planned behaviour. Postulated by Azjen (1991), [6] the theory of planned behaviour (TPB) is a generalised theory of human behaviour in social psychology literature that can be used to study a wide range of individual behaviours. It presumes that individual behaviour represents conscious reasoned choice, and is shaped by cognitive thinking and social pressures. The theory postulates that behaviours are based on one’s intention regarding that behaviour, which in turn is a function of the person’s attitude toward the behaviour, subjective norm regarding that behaviour, and perception of control over that behaviour (see Figure 4.2). Attitude is defined as the individual’s overall positive or negative feelings about performing the behaviour in question, which may be assessed as a summation of one’s beliefs regarding the different consequences of that behaviour, weighted by the desirability of those consequences. Subjective norm refers to one’s perception of whether people important to that person expect the person to perform the intended behaviour, and is represented as a weighted combination of the expected norms of different referent groups such as friends, colleagues, or supervisors at work. Behavioural control is one’s perception of internal or external controls constraining the behaviour in question. Internal controls may include the person’s ability to perform the intended behaviour (self-efficacy), while external control refers to the availability of external resources needed to perform that behaviour (facilitating conditions). TPB also suggests that sometimes people may intend to perform a given behaviour but lack the resources needed to do so, and therefore posits that behavioural control can have a direct effect on behaviour, in addition to the indirect effect mediated by intention.

TPB is an extension of an earlier theory called the theory of reasoned action, which included attitude and subjective norm as key drivers of intention, but not behavioural control. The latter construct was added by Ajzen in TPB to account for circumstances when people may have incomplete control over their own behaviours (such as not having high-speed Internet access for web surfing).

Innovation diffusion theory. Innovation diffusion theory (IDT) is a seminal theory in the communications literature that explains how innovations are adopted within a population of potential adopters. The concept was first studied by French sociologist Gabriel Tarde, but the theory was developed by Everett Rogers in 1962 based on observations of 508 diffusion studies. The four key elements in this theory are: innovation, communication channels, time, and social system. Innovations may include new technologies, new practices, or new ideas, and adopters may be individuals or organisations. At the macro (population) level, IDT views innovation diffusion as a process of communication where people in a social system learn about a new innovation and its potential benefits through communication channels—such as mass media or prior adopters— and are persuaded to adopt it. Diffusion is a temporal process—the diffusion process starts off slow among a few early adopters, then picks up speed as the innovation is adopted by the mainstream population, and finally slows down as the adopter population reaches saturation. The cumulative adoption pattern is therefore an s-shaped curve, as shown in Figure 4.3, and the adopter distribution represents a normal distribution. All adopters are not identical, and adopters can be classified into innovators, early adopters, early majority, late majority, and laggards based on the time of their adoption. The rate of diffusion also depends on characteristics of the social system such as the presence of opinion leaders (experts whose opinions are valued by others) and change agents (people who influence others’ behaviours).

At the micro (adopter) level, Rogers (1995) [7] suggests that innovation adoption is a process consisting of five stages: one, knowledge : when adopters first learn about an innovation from mass-media or interpersonal channels, two, persuasion : when they are persuaded by prior adopters to try the innovation, three, decision : their decision to accept or reject the innovation, four,: their initial utilisation of the innovation, and five, confirmation : their decision to continue using it to its fullest potential (see Figure 4.4). Five innovation characteristics are presumed to shape adopters’ innovation adoption decisions: one, relative advantage : the expected benefits of an innovation relative to prior innovations, two, compatibility : the extent to which the innovation fits with the adopter’s work habits, beliefs, and values, three, complexity : the extent to which the innovation is difficult to learn and use, four, trialability : the extent to which the innovation can be tested on a trial basis, and five, observability : the extent to which the results of using the innovation can be clearly observed. The last two characteristics have since been dropped from many innovation studies. Complexity is negatively correlated to innovation adoption, while the other four factors are positively correlated. Innovation adoption also depends on personal factors such as the adopter’s risk-taking propensity, education level, cosmopolitanism, and communication influence. Early adopters are venturesome, well educated, and rely more on mass media for information about the innovation, while later adopters rely more on interpersonal sources—such as friends and family—as their primary source of information. IDT has been criticised for having a ‘pro-innovation bias’—that is for presuming that all innovations are beneficial and will be eventually diffused across the entire population, and because it does not allow for inefficient innovations such as fads or fashions to die off quickly without being adopted by the entire population or being replaced by better innovations.

Elaboration likelihood model . Developed by Petty and Cacioppo (1986), [8] the elaboration likelihood model (ELM) is a dual-process theory of attitude formation or change in psychology literature. It explains how individuals can be influenced to change their attitude toward a certain object, event, or behaviour and the relative efficacy of such change strategies. The ELM posits that one’s attitude may be shaped by two ‘routes’ of influence: the central route and the peripheral route, which differ in the amount of thoughtful information processing or ‘elaboration required of people (see Figure 4.5). The central route requires a person to think about issue-related arguments in an informational message and carefully scrutinise the merits and relevance of those arguments, before forming an informed judgment about the target object. In the peripheral route, subjects rely on external ‘cues’ such as number of prior users, endorsements from experts, or likeability of the endorser, rather than on the quality of arguments, in framing their attitude towards the target object. The latter route is less cognitively demanding, and the routes of attitude change are typically operationalised in the ELM using the argument quality and peripheral cues constructs respectively.

Whether people will be influenced by the central or peripheral routes depends upon their ability and motivation to elaborate the central merits of an argument. This ability and motivation to elaborate is called elaboration likelihood . People in a state of high elaboration likelihood (high ability and high motivation) are more likely to thoughtfully process the information presented and are therefore more influenced by argument quality, while those in the low elaboration likelihood state are more motivated by peripheral cues. Elaboration likelihood is a situational characteristic and not a personal trait. For instance, a doctor may employ the central route for diagnosing and treating a medical ailment (by virtue of his or her expertise of the subject), but may rely on peripheral cues from auto mechanics to understand the problems with his car. As such, the theory has widespread implications about how to enact attitude change toward new products or ideas and even social change.

General deterrence theory. Two utilitarian philosophers of the eighteenth century, Cesare Beccaria and Jeremy Bentham, formulated general deterrence theory (GDT) as both an explanation of crime and a method for reducing it. GDT examines why certain individuals engage in deviant, anti-social, or criminal behaviours. This theory holds that people are fundamentally rational (for both conforming and deviant behaviours), and that they freely choose deviant behaviours based on a rational cost-benefit calculation. Because people naturally choose utility-maximising behaviours, deviant choices that engender personal gain or pleasure can be controlled by increasing the costs of such behaviours in the form of punishments (countermeasures) as well as increasing the probability of apprehension. Swiftness, severity, and certainty of punishments are the key constructs in GDT.

While classical positivist research in criminology seeks generalised causes of criminal behaviours, such as poverty, lack of education, psychological conditions, and recommends strategies to rehabilitate criminals, such as by providing them job training and medical treatment, GDT focuses on the criminal decision-making process and situational factors that influence that process. Hence, a criminal’s personal situation—such as his personal values, his affluence, and his need for money—and the environmental context—such as how protected the target is, how efficient the local police are, how likely criminals are to be apprehended—play key roles in this decision-making process. The focus of GDT is not how to rehabilitate criminals and avert future criminal behaviours, but how to make criminal activities less attractive and therefore prevent crimes. To that end, ‘target hardening’ such as installing deadbolts and building self-defence skills, legal deterrents such as eliminating parole for certain crimes, ‘three strikes law’ (mandatory incarceration for three offences, even if the offences are minor and not worth imprisonment), and the death penalty, increasing the chances of apprehension using means such as neighbourhood watch programs, special task forces on drugs or gang-related crimes, and increased police patrols, and educational programs such as highly visible notices such as ‘Trespassers will be prosecuted’ are effective in preventing crimes. This theory has interesting implications not only for traditional crimes, but also for contemporary white-collar crimes such as insider trading, software piracy, and illegal sharing of music.

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Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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2.2 Research Methods

Learning objectives.

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

• Recall the 6 Steps of the Scientific Method
• Differentiate between four kinds of research methods: surveys, field research, experiments, and secondary data analysis.
• Explain the appropriateness of specific research approaches for specific topics.

Sociologists examine the social world, see a problem or interesting pattern, and set out to study it. They use research methods to design a study. Planning the research design is a key step in any sociological study. Sociologists generally choose from widely used methods of social investigation: primary source data collection such as survey, participant observation, ethnography, case study, unobtrusive observations, experiment, and 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. When you are conducting research think about the best way to gather or obtain knowledge about your topic, think of yourself as an architect. An architect needs a blueprint to build a house, as a sociologist your blueprint is your research design including your data collection method.

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 wouldn’t stroll into a crime-ridden neighborhood at midnight, calling out, “Any gang members around?”

Making sociologists’ presence invisible is not always realistic for other reasons. That option is not available to a researcher studying prison behaviors, early education, or the Ku Klux Klan. Researchers can’t just stroll into prisons, kindergarten classrooms, or Klan meetings and unobtrusively observe behaviors or attract attention. In situations like these, other methods are needed. Researchers choose methods that best suit their study topics, protect research participants or subjects, and that fit with their overall approaches to research.

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

At some point, most people in the United States respond to some type of survey. The 2020 U.S. Census is an excellent example of a large-scale survey intended to gather sociological data. Since 1790, United States has conducted a survey consisting of six questions to received demographical data pertaining to residents. The questions pertain to the demographics of the residents who live in the United States. Currently, the Census is received by residents in the United Stated and five territories and consists of 12 questions.

Not all surveys are considered sociological research, however, and many surveys people commonly encounter focus on identifying marketing needs and strategies rather than testing a hypothesis or contributing to social science knowledge. Questions such as, “How many hot dogs do you eat in a month?” or “Were the staff helpful?” are not usually designed as scientific research. The Nielsen Ratings determine the popularity of television programming through scientific market research. However, polls conducted by television programs such as American Idol or So You Think You Can Dance cannot be generalized, because they are administered to an unrepresentative population, a specific show’s audience. You might receive polls through your cell phones or emails, from grocery stores, restaurants, and retail stores. They often provide you incentives for completing the survey.

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, think, and act—or at least how they say they feel, think, and act. Surveys can track preferences for presidential candidates or reported individual behaviors (such as sleeping, driving, or texting habits) or 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 college athletes, international students, or teenagers living with type 1 (juvenile-onset) diabetes. Most researchers choose to survey a small sector of the population, or a sample , a 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. As a result, a Gallup 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.

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 survey up front. 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, which is a means of gathering the information.

A common instrument is a questionnaire. Subjects often answer a series of closed-ended questions . The researcher might ask yes-or-no or multiple-choice questions, allowing subjects to choose possible responses to each question. This kind of questionnaire collects quantitative data —data in numerical form that can be counted and statistically analyzed. Just count up the number of “yes” and “no” responses or correct answers, and chart them into percentages.

Questionnaires can also ask more complex questions with more complex answers—beyond “yes,” “no,” or checkbox options. These types of inquiries use open-ended questions that require short essay responses. Participants willing to take the time to write those answers might convey personal religious beliefs, political views, goals, or morals. The answers are subjective and vary from person to person. How do you plan to use your college education?

Some topics that investigate internal thought processes 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 personal explanation is qualitative data —conveyed through words. 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 in-depth material that they provide.

An interview is a one-on-one conversation between the researcher and the subject, and it is a way of conducting surveys on a topic. 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 does 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. The researcher will also benefit from gaining a subject’s trust, from empathizing or commiserating with a subject, and from listening without judgment.

Surveys often collect both quantitative and qualitative data. For example, a researcher interviewing people who are incarcerated might receive quantitative data, such as demographics – race, age, sex, that can be analyzed statistically. For example, the researcher might discover that 20 percent of incarcerated people are above the age of 50. The researcher might also collect qualitative data, such as why people take advantage of educational opportunities during their sentence and other explanatory information.

The survey can be carried out online, over the phone, by mail, or face-to-face. When researchers collect data outside a laboratory, library, or workplace setting, they are conducting field research, which is our next topic.

Field Research

The work of sociology rarely happens in limited, confined spaces. 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. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In field work, the sociologists, rather than the subjects, are the ones out of their element.

The researcher interacts with or observes people and gathers 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 the DMV, a hospital, airport, mall, or beach resort.

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviors in that setting. Field work is optimal for observing how people think and behave. It seeks to understand why they behave that way. However, researchers may struggle to narrow down cause and effect when there are so many variables floating around in a natural environment. And while field research looks for correlation, its small sample size does not allow for establishing a causal relationship between two variables. Indeed, much of the data gathered in sociology do not identify a cause and effect but a correlation .

Sociology in the Real World

Beyoncé and lady gaga as sociological subjects.

Sociologists have studied Lady Gaga and Beyoncé and their impact on music, movies, social media, fan participation, and social equality. In their studies, researchers have used several research methods including secondary analysis, participant observation, and surveys from concert participants.

In their study, Click, Lee & Holiday (2013) interviewed 45 Lady Gaga fans who utilized social media to communicate with the artist. These fans viewed Lady Gaga as a mirror of themselves and a source of inspiration. Like her, they embrace not being a part of mainstream culture. Many of Lady Gaga’s fans are members of the LGBTQ community. They see the “song “Born This Way” as a rallying cry and answer her calls for “Paws Up” with a physical expression of solidarity—outstretched arms and fingers bent and curled to resemble monster claws.”

Sascha Buchanan (2019) made use of participant observation to study the relationship between two fan groups, that of Beyoncé and that of Rihanna. She observed award shows sponsored by iHeartRadio, MTV EMA, and BET that pit one group against another as they competed for Best Fan Army, Biggest Fans, and FANdemonium. Buchanan argues that the media thus sustains a myth of rivalry between the two most commercially successful Black women vocal artists.

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 whether 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 writer, or 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 experience a specific aspect of social life. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behavior. A researcher might work as a waitress in a diner, experience homelessness 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 analyzing data and generating results.

In a study of small towns in the United States 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 U.S. 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 the purpose of their study.

This shaped the structure of Middletown: A Study in Modern American Culture , their published results (Lynd & Lynd, 1929).

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 behaviors of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ behavior. 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 and describe 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, 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’s how Ehrenreich found herself joining the ranks of the working class. 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 working class 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.

The book she wrote upon her return to her real life as a well-paid writer, has been widely read and used in many college classrooms.

Ethnography

Ethnography is the immersion of the researcher in the natural setting of an entire social community to observe and experience their everyday life and culture. The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a social group.

An ethnographic study might observe, for example, a small U.S. fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or an amusement park. 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.

A sociologist studying a tribe in the Amazon might watch the way villagers go about their daily lives and then write a paper about it. To observe a spiritual retreat center, an ethnographer might sign up for a retreat and attend as a guest for an extended stay, observe and record data, and collate the material into results.

Institutional Ethnography

Institutional ethnography is an extension of basic ethnographic research principles that focuses intentionally on everyday concrete social relationships. Developed by Canadian sociologist Dorothy E. Smith (1990), institutional ethnography is often considered a feminist-inspired approach to social analysis and primarily considers women’s experiences within male- dominated societies and power structures. Smith’s work is seen to challenge sociology’s exclusion of women, both academically and in the study of women’s lives (Fenstermaker, n.d.).

Historically, social science research tended to objectify women and ignore their experiences except as viewed from the male perspective. Modern feminists note that describing women, and other marginalized groups, as subordinates helps those in authority maintain their own dominant positions (Social Sciences and Humanities Research Council of Canada n.d.). Smith’s three major works explored what she called “the conceptual practices of power” and are still considered seminal works in feminist theory and ethnography (Fensternmaker n.d.).

Sociological Research

The making of middletown: a study in modern u.s. culture.

In 1924, a young married couple named Robert and Helen Lynd undertook an unprecedented ethnography: to apply sociological methods to the study of one U.S. city in order to discover what “ordinary” people in the United States did and believed. Choosing Muncie, Indiana (population about 30,000) as their subject, they moved to the small town and lived there for eighteen months.

Ethnographers had been examining other cultures for decades—groups considered minorities or outsiders—like gangs, immigrants, and the poor. But no one had studied the so-called average American.

Recording interviews and using surveys to gather data, the Lynds objectively described what they observed. Researching existing sources, they compared Muncie in 1890 to the Muncie they observed in 1924. Most Muncie adults, they found, had grown up on farms but now lived in homes inside the city. As a result, the Lynds focused their study on the impact of industrialization and urbanization.

They observed that Muncie was divided into business and working class groups. They defined business class as dealing with abstract concepts and symbols, while working class people used tools to create concrete objects. The two classes led different lives with different goals and hopes. However, the Lynds observed, mass production offered both classes the same amenities. Like wealthy families, the working class was now able to own radios, cars, washing machines, telephones, vacuum cleaners, and refrigerators. This was an emerging material reality of the 1920s.

As the Lynds worked, they divided their manuscript into six chapters: Getting a Living, Making a Home, Training the Young, Using Leisure, Engaging in Religious Practices, and Engaging in Community Activities.

When the study was completed, the Lynds encountered a big problem. The Rockefeller Foundation, which had commissioned the book, claimed it was useless and refused to publish it. The Lynds asked if they could seek a publisher themselves.

Middletown: A Study in Modern American Culture was not only published in 1929 but also became an instant bestseller, a status unheard of for a sociological study. The book sold out six printings in its first year of publication, and has never gone out of print (Caplow, Hicks, & Wattenberg. 2000).

Nothing like it had ever been done before. Middletown was reviewed on the front page of the New York Times. Readers in the 1920s and 1930s identified with the citizens of Muncie, Indiana, but they were equally fascinated by the sociological methods and the use of scientific data to define ordinary people in the United States. The book was proof that social data was important—and interesting—to the U.S. public.

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 a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study as a method is that while offering depth on a topic, it 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 contribute tremendous insight. 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, which are elements crucial to a “civilized” child’s development. These children mimic the behaviors and movements of animals, and often invent their own language. There are only about one hundred 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” growth and nurturing. 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 Ukranian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, and she ate raw meat and scraps. Five years later, a neighbor 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 behaviors, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2011). Case studies like this offer a way for sociologists to collect data that may not be obtained by any other method.

Experiments

You have probably tested some of your own 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 more data can be recorded in a limited amount of time. In a natural or field- based experiment, the time it takes to gather the 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 (cause), then another particular thing will result (effect). To set up a lab-based experiment, sociologists create artificial situations that allow them to manipulate variables.

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. To test the benefits of tutoring, for example, the sociologist might provide tutoring to the experimental group of students but not to the control group. Then both groups would be tested for differences in performance to see if tutoring 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 of a student, for example.

And if a researcher told the students they would be observed as part of a study on measuring the effectiveness of tutoring, the students might not behave naturally. This is called the Hawthorne effect —which occurs when people change their behavior because they know they are being watched as part of a study. The Hawthorne effect is unavoidable in some research studies because sociologists have to make the purpose of the study known. Subjects must be aware that they are being observed, and a certain amount of artificiality may result (Sonnenfeld 1985).

A real-life example will help illustrate the process. In 1971, Frances Heussenstamm, a sociology professor at California State University at Los Angeles, had a theory about police prejudice. To test her theory, she conducted research. She chose fifteen students from three ethnic backgrounds: Black, White, and Hispanic. She chose students who routinely drove to and from campus along Los Angeles freeway routes, and who had had perfect driving records for longer than a year.

Next, she placed a Black Panther bumper sticker on each car. That sticker, a representation of a social value, was the independent variable. In the 1970s, the Black Panthers were a revolutionary group actively fighting racism. Heussenstamm asked the students to follow their normal driving patterns. She wanted to see whether seeming support for the Black Panthers would change how these good drivers were treated by the police patrolling the highways. The dependent variable would be the number of traffic stops/citations.

The first arrest, for an incorrect lane change, was made two hours after the experiment began. One participant was pulled over three times in three days. He quit the study. After seventeen days, the fifteen drivers had collected a total of thirty-three traffic citations. The research was halted. The funding to pay traffic fines had run out, and so had the enthusiasm of the participants (Heussenstamm, 1971).

Secondary Data Analysis

While sociologists often engage in original research studies, they also contribute knowledge to the discipline through secondary data analysis . Secondary data does not result from firsthand research collected from primary sources, but are the already completed work of other researchers or data collected by an agency or organization. Sociologists might study works written by historians, economists, teachers, or early sociologists. They might search through periodicals, newspapers, or magazines, or organizational data from any period in history.

Using available information not only saves time and money but can also 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 behavior 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 social media.

Social scientists also learn by analyzing the research of a variety of agencies. Governmental departments and global groups, like the U.S. Bureau of Labor Statistics or the World Health Organization (WHO), publish studies with findings that are useful to sociologists. A public statistic like the foreclosure rate might be useful for studying the effects of a recession. A racial demographic profile might be compared with data on education funding to examine the resources accessible by different groups.

One of the advantages of secondary data like old movies or WHO statistics is that it is nonreactive research (or unobtrusive research), meaning that it does not involve direct contact with subjects and will not alter or influence people’s behaviors. 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 will need to do some legwork to track them down and gain access to records. To guide the search through a vast library of materials and avoid wasting time reading unrelated sources, sociologists employ content analysis , applying a systematic approach to record and value information gleaned from secondary data as they relate to the study at hand.

Also, in some cases, there is no way to verify the accuracy of existing data. It is easy to count how many drunk drivers, for example, 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 survey the topic from the precise angle the researcher seeks. For example, the average salaries paid to professors at a public school is public record. But these 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’ve been teaching.

When conducting content 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, when Robert S. Lynd and Helen Merrell Lynd gathered research 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 insights about small U.S. communities. Today, it is an illustration of 1920s attitudes and values.

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• Knowledge Base

Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in  if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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3 Social science theories, methods, and values

Learning Objectives for this Chapter

After reading this Chapter, you should be able to:

• understand, apply, and evaluate core social science values, concepts, and theories, which can help inform and guide our understanding of how the world works, how power is defined and exercised, and how we can critically understand and engage with these concepts when examining the world around us.

Social science theory: theories to explain the world around us

As we have discussed in previous chapters, social science research is concerned with discovering things about the social world: for instance, how people act in different situations, why people act the way they do, how their actions relate to broader social structures, and how societies function at both the micro and macro levels. However, without theory, the ‘social facts’ that we discover cannot be woven together into broader understandings about the world around us.

Theory is the ‘glue’ that holds social facts together. Theory helps us to conceptualise and explain why things are the way they are, rather than only focusing on how things are. In this sense, different theoretical perspectives, such as those discussed in this Chapter, act as different lenses through which we can see and interpret the world around us.

Theory testing and generation is also an important part of social scientific research. As shown in the image below, different theories are rooted in different philosophical foundations. That is, various theories arise in accordance with different ways of seeing and living in the world, as well as different understandings about how knowledge is understood and constructed. As we learned earlier in the book, these concern both ontological and epistemological considerations, but also axiological considerations; that is, questions about the nature of value,  and what things in the world hold value (including in relation to one another). While theory is rooted in these philosophical foundations, however, it also gives way to different ways of doing research, both in terms of the methodology and methods employed. Overall, using different theoretical perspectives to consider social questions is a bit like putting on different pairs of glasses to see the world afresh.

Below we consider some foundational social science theories. While these are certainly not the only  theoretical perspectives that exist, they are often considered to be amongst the most influential. They also provide helpful building blocks for understanding other theoretical perspectives, as well as how theory can be applied to guide and build social scientific knowledge.

Structural functionalism

Structural functionalism is a theory about social institutions, ‘social norms’ (i.e., the often unspoken rules that govern social behaviours), and social stability. We talk more about social institutions in the next Chapter of this book, but essentially they are the ‘big building blocks’ of society that act as both repositories and creators/instigators of social norms. These include things like school/education, the state (often called a meta-institution), the family, the economy, and more. In this regard, structural functionalism is considered a macro theory; that is, it considers macro (large) structures in society, and concerns how they work in an interdependent way to produce what structural functionalists believe to be ‘harmonious’ and stable societies. Structural functionalists are particularly concerned with social institutions’ manifest and latent functions, as well as their functions and dysfunctions (Merton [1910-2003]).

Manifest functions of social institutions include things that are overt and obvious. By contrast, latent functions of social institutions are those that are more hidden or secondary. For instance, a manifest function of the social institution of school is to teach students new knowledge and skills, which can assist them to move into chosen careers. Alternatively, we might also argue that school has other latent functions, such as socialisation and conformity to social norms, and building relationships with peers.

In addition to manifest and latent functions, structural functionalists are also concerned with the  functions  and  dysfunctions  of social institutions. They believe, for instance, that dysfunctions play just as much of an important role as functions, because they enable social institutions to identify and punish them, thereby making an example of dysfunctional elements (e.g., punishing those committing crime). This serves to reinforce social norms around how society should function.

Reflection exercise

Take a piece of paper and, in your own words, write down a brief definition of structural functionalism. Then re-read the above sub-section. How does your understanding fit with the information above?

Structural functionalism: want to learn more?

If you’d like to reinforce your understanding of structural functionalism, the below video provides a good summary that might be helpful.

Functionalism (YouTube, 5:40) :

Phenomenology

Phenomenology is the study of our experiences and how our consciousness makes sense of the phenomena (be they objects, people or ideas) around us. As a methodology or approach in the social sciences it has garnered renewed interest in the last few decades to better understand the world around us by studying how we experience the world in a subjective and often individual manner. It is, thus, considered a ‘micro’ theory.

This philosophical approach was developed by Edmund Husserl (1859–1938), and his students and critics in France and Germany (key figures were philosophers Martin Heidegger (1889-1976), Jean-Paul Sartre (1905-1980) and Maurice Merleau-Ponty (1908-1961)) and later made it to the US via influential sociologists, such as Alfred Schütz (1899–1959).

Phenomenologists reject objectivity and instead focus on the subjective and intersubjective, the relations between people, and between people and objects. So, rather than trying to come to some objective truth, they are more interested in relationships and connections between the individual and the world around them. Indeed, there is a strong centering of and focus on the individual and their experiences of the world that phenomenologists believe can tell us about society at large. The individual is also key, as there is a focus on the sensory and the body both as instruments of enquiring as well as enquiry. Thus, we are always already part of the world around us and have to make sense of being here, but also want to go beyond ourselves by understanding others and how they relate to the world. The body features as a key site for such enquiries as it is the physical connection we have with people and objects around us. Further, there is a focus on everyday, mundane experiences as they have much to tell us about how society operates. This background environment in which we as people operate is called a lifeworld,  the shared horizon of experience we share and inhabit. It is marked by linguistic, cultural, and social codes and norms.

One key method inherent to Husserl’s early approaches is ‘bracketing’ , the process of standing back or aside from phenomena to understand it better. Such processes of ‘reflexivity’ and understanding our taken for granted attitudes and beliefs about certain phenomena are crucial to enable the social sciences to better understand the world around us. Debates in philosophy continue around whether such a bracketing is ever fully possible, especially considering that we as humans remain trapped in our minds and  bodies. Nonetheless, phenomenology has had a profound impact in most social sciences to redirect the focus towards the intersubjective nature of life and the lifeworld, within which we experience the world around us.

Take a piece of paper and, in your own words, write down a brief definition of phenomenology. Then re-read the above sub-section. How does your understanding fit with the information above?

Phenomenology: want to learn more?

If you’d like to reinforce your understanding of phenomenology, the below video provides a good summary that might be helpful.

Understanding Phenomenology (YouTube, 2:59) :

Symbolic interactionism

Symbolic interactionism is related to phenomenology as it is also a theory focused on the self. In this regard, it’s also a micro theory – it has particular focus on individuals and how they interact with one another. Symbolic interactionists say that symbolism is fundamental to how we see ourselves and how we see and interact with others. George Herbert Mead (1863-1931) is often regarded as the founder of this theory and his focus was on the relationship between the self and others in society. He considered our individual minds to function through interactions with others and through the shared meanings and symbols we create for the people and objects around us. Mead’s best known book Mind, Self, Society, was posthumously put together by his students and demonstrates how our individual minds allow us to use language and symbols to make sense of the world around us and how we construct a self based on how others perceive us.

Charles Cooley’s (1864-1929) concept of the “ looking glass self ” points out, for instance, that other peoples’ perceptions of us can also influence and change our perceptions of ourselves. Other sociologists, such as Erving Goffman (1922-1982), have built on this understanding, suggesting that ‘all of life is a stage’ and that each of us play different parts, like actors in a play. Goffman argued that we adapt our personality, behaviours, actions, and beliefs to suit the different contexts we find ourselves in. This understanding is often referred to as a ‘dramaturgical model’ of social interaction; it understands our social interactions to be performative – they are the outcomes of our ‘play acting’ different roles.

In explaining this theory, Goffman also referred to what he called ‘impression management’. As part of this, for instance, Goffman drew a crucial distinction between what he referred to as our ‘ front stage selves ‘ and our ‘ backstage selves ‘. For Goffman, our ‘front stage selves’ are those that we are willing to share with the ‘audience’ (e.g., the person or group with whom we are interacting). Alternatively, our ‘backstage selves’ are those that we keep for ourselves; this is the way we act when we are alone and have no audience.

Goffman also pointed to the important role that stigma can play in how we see ourselves and thus, how we act and behave in relation to others. Stigma occurs when “the reaction of others spoils normal identity”. Goffman argued that those who feel stigmatised by others (e.g., through public discourses and ‘frames’ of social issues that vilify certain groups of people) also experience changes in the way they see themselves – that is, their own sense of self-identity is ‘spoiled’. This can lead to other negative effects, such as social withdrawal and poorer health and wellbeing.

Take a piece of paper and, in your own words, write down a brief definition of symbolic interactionism. Then re-read the above sub-section. How does your understanding fit with the information above?

This exercise is to be conducted in small groups. First, get into a small group with other students. Then, do the following:

• Think about your daily life, activities, and interactions with others.
• Take a few moments to identify at least three examples of social symbols that you and other group members frequently use to interpret the world around you.
• Talk about how each of the group members interprets/responds to these symbols. Are there similarities? Are there differences?

Students should share/discuss their thoughts within the group, and if undertaken in a class environment, then report back to the class.

Symbolic interactionism: want to learn more?

If you’d like to reinforce your understanding of symbolic interactionism, the below videos provide good summaries that might be helpful.

Symbolic Interactionism (YouTube, 3:33) provides an easy-to-understand summary of symbolic interactionism:

What does it mean to be me? Erving Goffman and the Performed Self (YouTube, 1:58) provides a helpful summary of Erving Goffman’s conception of the ‘performed self’ – including his notions of a ‘front stage’ and ‘backstage’ self:

Conflict theories

Conflict theories focus particularly on conflict within and across societies and, thus, are particularly interested in power: where it does and doesn’t exist, who does and doesn’t hold it, and what they do or don’t do with it, for example. These theories hold that societies will always be characterised by states of conflict and competition over goods, resources, and more. These conflicts can arise along various lines, though

this group of theories emanate from the work of Karl Marx (1818-1883), who saw the capitalist economy as a primary site of conflict.

In Marx’s view, social ills emanated particularly from what he described as an upper- and lower-class structure, which had been perpetuated across multiple societies (e.g., in ancient societies in terms of slave owners/slaves, or in pre-Enlightenment times between the feudal peasantry/aristocracy). He saw capitalism as replicating this upper/lower class structure through the creation of a bourgeoisie (upper class, who own the means of production) and proletariat (lower class, who supply labour to the capitalist market). Marx also talked about a lumpenproletariat , an underclass without class consciousness and/or organised political power. Classical Marxism takes a macro lens: it is particularly concerned with how power is invested in the social institution of the capitalist economy. In this sense, classical Marxism represents a structural theory of power.

Marx argued that the only way for society to be fairer and more equal was if the proletariat was to rise up and revolt against the bourgeoisie; to “smash the chains of capitalism”! Thus, he strongly advocated for revolution as a means of creating a fairer, utopic society. He stated, “Philosophers have hitherto only interpreted the world, in various ways; the point is to change it” (Marx 1968: 662). Nevertheless, a series of revolutions in the early 20th century that drew on Marxist thinking resulted in power vacuums that made way for violent, totalitarian regimes, as political philosopher Hannah Arendt (1906-1975) argued in On the Origins of Totalitarianism . On this basis, subsequent conflict theorists (and critical theorists) have tended towards advocating for more incremental reforms, as opposed to revolution.

Take a few moments to watch the below two videos, which explain conflict theory in greater detail.

Key concepts: Conflict theory – definition and critiques (YouTube, 2:49) :

Political theory – Karl Marx (YouTube, 9:27) :

After watching these videos, take a piece of paper and, in your own words, write down a definition of conflict theories. After doing so, re-read the above sub-section. How does your understanding fit with the information in the above sub-section, and in the videos? Was anything missing? Is anything still unclear?

Critical theories

Marx saw the capitalist economy as a primary site of oppression, between the working class and the property owning class. Marx advocated for revolution, where the proletariat were urged to rise up and break the chains of capitalism by overthrowing the bourgeoisie. Marx saw this as being necessary for ensuring the freedom of the working classes. Critical theory develops from the work of Karl Marx, supplementing his theory of capitalism with other sociological and philosophical concepts.

Gramsci and cultural hegemony

In addition to Marx, critical theory utilised the work of Italian political philosopher Antonio Gramsci, specifically his concept of ‘Cultural Hegemony’. When we refer to ‘hegemonic’ social norms, we’re referring to social norms that are regarded as ‘common sense’ and thus, which overshadow and suppress alternative norms. Hegemonic norms typically reflect the values of the ruling classes (in Marxist terms, the bourgeoisie). To learn more, you might like to watch the video below:

Hegemony: WTF? An introduction to Gramsci and cultural hegemony (YouTube, 6:25)

Developing from this, critical theory also considers how power and oppression can operate in more subtle ways across the whole of society. Critical theory does not seek to actively bring about revolution, as the possibility for a revolution in the years post-World War Two was unlikely. Whilst critical theorists are by no means opposed to revolution, their focus lies more in identifying how capitalist society and its institutions limits advancement of human civilisation. In this respect, conflict theorists see more opportunities for praxis than classical Marxists.

Critical theory observes how the Enlightenment ideals of freedom, reason, and liberalism have developed throughout the first half of the 1900s. Ultimately, critical theorists see that reason has not necessarily progressed in a positive way throughout history. In fact, reason has developed to become increasingly technical, interested in classifying, regulating, and standardising all aspects of human society and culture. German philosopher Theodor Adorno (1903-1969) thought that Nazi Germany and the holocaust is a devastating example of the potential evils of rationality if developed without a critical perspective.

Another, less extreme, example of this tendency toward standardisation is in the production of art and culture. Big budget films, typically in the superhero or science fiction genre, all appear to be virtually identical: extravagant special effects, epic soundtracks, and relatively simple plots. However, this is not to say that such films are of a poor quality. Rather the similarity and popularity of these films indicates a homogenisation of culture. If culture is merely the reproduction of the same, how can society progress beyond its current point?

This critique of the development of reason throughout the 20th century does not mean that we must abandon reason entirely. To do so would be to discount the vast wealth of knowledge that humanity has come to grasp, as well as prevent further knowledge production. Instead, critical theorists argue that reason should be critiqued to uncover what has been left out of its development thus far, as well as open up the possibility for a more free, progressive form of society.

At its core, then, critical theory can be thought about as being an additional theoretical lens through which we can look at and understand the social world around us. In tune with Flyvbjerg’s (2001) conception of phronetic social science, critical theorists are also concerned with disrupting the systems they observe as a means of achieving social change. Critical theory urges us to recognise, understand and address how capitalist society reproduces itself and limits the free organisation of human beings.

Take a few moments to watch Critical theory definition and critiques (YouTube, 3:26) , which explains critical theory in greater detail.

Take a piece of paper and, in your own words, write down a brief definition of critical theories. Then re-read the above sub-section. How does your understanding fit with the information above and the video?

Critical theory can be applied in myriad different ways to better understand the world around us. In  Critical theory and the production of mass culture (YouTube, 2:12) , critical theory is adopted as a lens to understand and critique the production of mass culture. Watch the video and then consider the questions below.

• Can you think of examples where you could argue that the primary objective of producing art is to preserve the economic structure of the capitalist system?
• Do you agree with the proposition that mass-consumed entertainment, like popular television shows, are only  produced as a source of light entertainment and escapism from work, and thus serve to placate and pacify the worker? Why or why not? (What other  purposes might such entertainment serve, if any?)
• Do you agree with Adorno’s proposition that the products of the ‘culture industry’ are not only the artworks, but also the consumers themselves? Why or why not?

Critical race theory

Critical race theory applies a critical theory lens to the notion of race, seeking to understand how the concept of race itself can act as a site of power and oppression. Arising from the work of American legal scholars during the 1980s (including key thinkers like Derrick Bell [1930-2011] and Kimberlé Crenshaw [1959-]), it originally sought to understand and challenge “the ways in which race and racial power [were]… cosnstructed and represented in American legal culture and, more generally, in American society as a whole.” (Crenshaw et al. 1995: xiii) In particular, it questioned whether the civil rights afforded to African Americans in the aftermath of the civil rights movement had made a substantive impact on their experiences of social justice. Critical race theorists argued that more needed to be done; that civil rights had not had the desired impacts because (amongst other reasons) they:

• were imagined, shaped and brought into being by (predominantly) white, male middle- or upper-class lawyers, and thus, were only imagined within the bounds of white ontology,
• did not move beyond race – race still mattered, and
• implicitly perpetuated white privilege (e.g. they were constrained to only imagine redress and justice within the existing oppressive, white hegmonic system).

Crenshaw (1995: xiii) writes that, although critical race scholars’ work is heterogenous, they are nevertheless united by the following common interests:

• “The first is to understand how a regime of white supremacy and its subordination of people of color have been created and maintained in America, and, in particular, to examine the relationship between that social structure and professed ideas such as ‘the rule of law’ and ‘equal protection’.”
• “The second is a desire not merely to understand the vexed bond between law and racial power but to change it.”

In Australia, scholars have also taken up aspects of a critical race lens to understand how privilege is bound up with race. As Moreton-Robinson (2015: xiii) puts it, in Australia:

Race matters in the lives of all peoples; for some people it confers unearned privileges, and for others it is the mark of inferiority. Daily newspapers, radio, television, and social media usually portray Indigenous peoples as a deficit model of humanity. We are overrepresented as always lacking, dysfunctional, alcoholic, violent, needy, and lazy… For Indigenous people, white possession is not unmarked, unnamed or invisible; it is hypervisible…

Crenshaw has been crucial in also stressing the key importance of understanding how race can also intersect with other aspects of social identity, such as gender, to produce a ‘double’ or ‘triple’ oppression. In Australia, Professor Aileen Moreton-Robinson’s 2000 book, Talkin’ up to the white woman, was also crucial in understanding how Australian feminism could also be oppressive of Indigenous Australian women by not seeing and hearing them or the specific issues they face/d. She called for the need for “white feminists to relinquish some power, dominance and privilege in Australian feminism to give Indigenous women’s interest some priority” (Moreton-Robinson 2000: xxv). This emphasised that an intersectional lens was needed to acknowledge the different but cumulative impacts of both racial oppression and sexism. At the centre of this argument is the reality that “all white feminists [in Australia] benefit from colonisation; they are overwhelmingly represented and disproportionately predominant, have the key roles, and constitute the norm, the ordinary and the standard of womanhood in Australia” (Moreton-Robinson 2000: xxv).

Uproar over critical race theory

During 2020, racial sensitivity training in the USA prompted widespread discussion about critical race theory. Former US President, Donald Trump, posits in the video below that the theory, and the kinds of racial sensitivity training it promotes, are fundamentally racist – against white people. Others argued that this represented a deep misunderstanding of the theory, but also an ignorance of the extent and power of white privilege.

For an example of former President Trump’s views, watch  Trump: Racial sensitivity training on white privilege is ‘racist’ (YouTube, 3:16) :

Postmodern critique of critical race theory

Postmodernists have levelled critique at critical race theory on the basis that understanding/explaining power as being rooted in racial difference has the consequence of reinforcing and perpetuating the validity of ‘race’. Postmodernism, however, rejects the distinct, conceptual bounds of ‘race’ and racialised identities. Instead, it sees race itself as a social construction, which should be questioned and disrupted, thereby leading to new insights that aren’t constrained by socially constructed definitions of race.

Kwame Anthony Appiah, for example, seeks to “probe the very definitions of race itself. He bypasses the empirical question of whether racism exists to ask the theoretical question of what race and racism are” (in Chong-Soon Lee 1995: 441)

Take a piece of paper and, in your own words, write down a brief definition of critical race theory . Then re-read the above sub-section. How does your understanding fit with the information above?

Putting theory into action: rethinking crime through a critical lens

Critical criminologists apply a critical theory lens to the study of crime and criminality. In this regard, critical criminology is concerned with understanding how the criminal justice system can act as a site of power and oppression; a perspective that tends to sit in contrast with western (non-critical) criminology, which sees the criminal justice system as a natural social institution that has the primarily purpose of protecting society against deviants (criminals) and making an example of those who fail to comply with hegemonic social norms. (This non-critical view draws parallels, for example, with the perceived ‘functions’ of the criminal justice system under a structural functionalist perspective, and its role in making examples of ‘dysfunctional’ elements of society.)

Critical criminologists in Australia have considered the role of the criminal justice system as a key site of oppression under, for example, Australian settler colonialism. For instance, Indigenous Australians are, per capita, the most incarcerated peoples in the entire world ( Anthony & Baldry 2017 ) and these incarceration rates are rising, not reducing (ABS 2018). In using a critical lens to understand the difference between incarceration rates for Indigenous and non-Indigenous Australians, however, we can seek better insight into how the criminal justice system operates as a site of oppression, perpetuating white settler colonial norms and values, which seek to punish alternative ontologies and epistemologies. Lynch (cited in Cunneen and Tauri 2016: 26) argued,

In short, criminology is one of the disciplines that established the conditions necessary for maintenance of the status quo of power. It can only do so by oppressing those who would undermine the status quo. In this sense, criminology must be viewed as a science of oppression.

In part, this oppression operates through the construction of knowledge and truth within (positivist) criminology (which relates to Foucault’s conception of power-knowledge, as we touched on last week). In turn, this also involves what Cunneen and Tauri (2016: 26) describe as “the ideologically driven dismissal of Indigenous knowledge about the social world as ‘subjective’, ‘unscientific’, and/or at best ‘folk epistemology’… which in turn paves the way for excluding other ways of knowing from the Western, criminological lexicon”.

In their book, Decolonising criminology, Blagg and Anthony (2019: 22-23) set out a taxonomy for what they see as a decolonised criminology (noting, though, that Blagg and Anthony themselves are non-Indigenous researchers, though they have worked closely with Indigenous peoples and communities for decades).  In their taxonomy (which we have included an adapted version of below), they include the following probing comparisons between a positivist (largely uncritical) criminology and a decolonised (critical) criminology:

A table comparing positivist and decolonial approaches to criminology.

Source: Authors’ adaptation from Blagg & Anthony (2019: 22-23 )

The probes and questions that Blagg & Anthony pose in the above taxonomy are critical in their focus and intent; they seek to critique the criminal justice system as a site of colonial power, but they also seek to change it — through research that produces knowledge about these truths. This is, in essence, a reframing (to use Bacchi’s term) of the nature of criminological research towards a richer, and more historically and culturally contextualised understanding of the Australian criminal justice system. As a result, this produces different knowledge about crime and justice in Australia: knowledge that shifts blame away from the individual (the ‘bad’ Indigenous citizen, to use Moreton-Robinson’s [2009] language) to the structures, history and continuation of colonial oppression.

Critical or radical criminology?

Radical criminology is rooted in the Marxist conflict tradition and sees the capitalist economy as being central to the definitions of crime (arrived at by the bourgeoisie) that constrict, control and suppress the working classes (proletariat).

In contrast (or in addition to), critical criminology is interested in more than just class relations and also sees different opportunities for praxis – tending to favour a more incremental approach to social change as opposed to widespread revolution ( Bernard 1981 )

Drawing on a critical criminology and decolonising perspective, consider the below graph, which shows the over-representation of Indigenous Australians in prisons, indicating an upward trend from 2008-2018. Then consider, from a critical criminology standpoint, what kinds of ‘truths’ might you draw on to help explain this trend?

(To guide your thinking, you may like to revisit the above taxonomy by Blagg and Anthony.)

Watch the below short clip of Senator Patrick Dodson talking in March 2021 about the issue of Aboriginal and Torres Strait Islander deaths in custody. Consider LNP Senator, Amanda Stoker’s response to Senator Pat Dodson, in particular her comment that she “understand[s] the outrage is real… because the lives of every person, though our justice system are important, no matter the colour of their skin.”

In #Estimates , @SenatorDodson fires up over a lack of action on deaths in custody. @stoker_aj ‘s response: “I understand the outrage is real…because the lives of every person, through our justice system are important, no matter the colour of their skin.” #Auspol @SBSNews @NITV pic.twitter.com/jgsb8y9YcD — Naveen Razik (@naveenjrazik) March 26, 2021

What do you think about Senator Stoker’s response to Senator Dodson? How might you analyse her response, through a critical race theory lens?

Choose one of the following social issues:

• The gender pay gap
• The workplace ‘stress’ epidemic
• Homelessness
• Childhood obesity

Consider how your chosen social issue might be explained by drawing on the different theoretical perspectives outlined earlier in this Chapter. Record your thoughts in a short, written explanation.

Reflection exercise: a critical reading of meritocracy

Kim and Choi (2017: 112) define meritocracy as “a social system in which advancement in society is based on an individual’s capabilities and merits rather than on the basis of family, wealth, or social background.” According to Kim and Choi (2017: 116), meritocracy has two key features: “impartial competition” and “equality of opportunity”.

The notion of meritocracy has arisen over the past few centuries primarily in response to feudalism and absolute monarchy, where power and privilege are handed down on the basis of familial lines (‘nepotism’) or friendships (‘cronyism’). This kind of system could (and often did) place people into positions of power, regardless of whether they were the most appropriate or ‘best’ person for the job. In essence, then, the notion of meritocracy is intended to tie social advancement to merit; that is, the focus is supposed to be on ‘what you know’ rather than ‘who you know’, which seems a noble cause, right? Many have argued, however, that a blinkered belief in meritocracy leaves a lot of things out of the ‘frame’.

The belief in meritocracy, and its focus on ‘what you know’ rather than ‘who you know’, can have both positive and negative impacts. Take a piece of paper and write a short list of each.

If critical theory operates according to the broad Marxist understanding of history as class struggle, post-structuralism is a theory that attempts to abandon the idea of grand historical narratives altogether. Fundamentally, post-structuralism differs from other social theories in its rejection of metanarratives , its critique of binaries, and its refusal to understand all human action as being shaped solely by universal social structures. Whilst there is much disagreement between post-structuralist thinkers, these three broad trends help us to understand this social theory.

Post-structuralism

Post-structural accounts of conflict and power can take a macro and micro lens. They see power as transcending social structures, like social institutions (e.g., the state, the economy) and instead being all around us at all times. Michel Foucault (1926-1984), for example, argued that power is everywhere and acts upon us to shape our identities, bodies, behaviours, and being. In terms of a liberal democratic society, therefore, where coercive (‘sovereign’) power is only exerted by the state under certain specific circumstances, Foucault argued that the state otherwise uses its power to create ‘responsibilised’ citizens who absorb hegemonic (i.e. authoritative/dominant) social norms and use these to govern themselves . This relates to what Fairclough (1995: 257) referred to as power by consent:

We live in an age in which power is predominantly exercised through the generation of consent rather than through coercion… through the inculcation of self-disciplining practices rather than through the breaking of skulls (though there is still unfortunately no shortage of the latter).

Foucault was also particularly interested in the link between power and knowledge. He argued that those who hold the power tend to construct knowledge and ‘truth’ in certain ways, which can reinforce their power by, for example, perpetuating certain social norms. This is elaborated on by Watts and Hodgson (2019) in reading 5.2, where they describe Foucault’s conception of power/knowledge as follows:

Truth is not neutral or objective, and is not simply a thing that can be verified scientifically because its ‘truth value’ is dependent on the operation and circulation of power (think, for example, the oft-quoted phrase that ‘truth is whatever the powerful say it is’). In the context of the human and social sciences, power creates knowledge and is also a force for the translation of knowledge of and about human beings into practice… For example, the moment we speak into existence the concept of something as commonplace as ‘human being’ or ‘human rights’ or ‘social justice’ we are using some form of power (truth) to render such things thinkable and knowable as things in the world (Watts and Hodgson 2019: 85-86).

Take a piece of paper and, in your own words, write down a brief definition of Foucault’s post-structural concept of power. Then, re-read the above account. Does your definition align with the information above?

Beck and Risk Society

The notion of risk society is outlined by Ulrich Beck in his 1992 book ‘Risk Society: Towards a New Modernity’. Where society was once organised around wealth distribution based on scarcity, Beck argues that society is becoming increasingly based on the distribution of risks. Risks are defined as “a systematic way of dealing with hazards and insecurities induced and introduced by modernization itself” (Beck 1992: 21). Beck argues that the process of modernisation is no longer focused exclusively on the creation of new technologies, but rather the focus lies in the management of risks of potential technologies. As such, modernisation is becoming increasingly reflexive, involved not only in the production of technologies to meet needs, but rather investigating the often unknown side-effects of technologies. For example, a nuclear energy plant might be built in order to meet society’s increasing energy demand. However, this solution to a specific problem then must deal with the new issue of disposing of this radioactive waste that modernisation itself has produced. This is just one example of the ecological risks inherent with the development of new technologies, which often have unintended side-effects, that must themselves be uncovered and solved.

Postmodernism

Before we can get to postmodernism, we need to define modernism to see what postmodernism wants to supersede. Modernism describes the social upheaval and major changes of 20th century life. It is marked by processes of industrialisation, rationalisation and bureaucratisation – in short a world in which the sciences seemed to provide ever more answers and ultimate truths about the world and us. Modernism or modernity was also about hope for a new society, unfettered technological and material progress and, with advances in scientific fields, led to longer lives and new and exciting materials to make new things to make life easier (think household machines). It was also punctured by some key social movements that brought the world to the brink of destruction in the epic fight over what ultimate truth should prevail. The key political ideologies of fascism, socialism and liberalism clashed in the second World War over their different visions for a new world order. In the post war climate of a new stand-off between socialism/communism and liberalism or the Soviet bloc and ‘the West’ many writers, academics and artists became disillusioned with the modernist project. Slowly critiques of these universalising truths and meta-narratives came to think of this time as a time of postmodernism. Jean-François Lyotard (1924-1998) defined postmodernism as the ‘incredulity towards meta-narratives’, by which he meant that increasingly people were no longer persuaded by grand or master narratives about themselves, a particular nation, people or even humanity. The singular, stable, coherent modern subject was thrown into a void and thus becomes fragmented, fluid and plural in the postmodern. No one truth exists anymore and the certainty of facts becomes disputed and muddied once more. Thus, postmodernity is about scepticism, deconstruction and questioning rather than offering answers and solutions. This has made it a controversial theory or topic as it offers little in the way of hope for a better world, indeed it is often seen as dystopic. Inherent in many postmodern critiques of current society is a critique of (late) capitalism and consumer or mass culture that pervade every aspect of our lives, whilst others focus on technology and its pervasive intrusion into our daily lives.

Resources for further learning

• Moreton-Robinson, A. 2015. ‘Introduction: white possession and Indigenous sovereignty matters.’ In. Moreton-Robinson, A.  The White Possessive: property, power and Indigenous sovereignty,  pp. xi-xxiv.
• Powers, C. 2009. Sociology as a coherent discipline: unifying themes. In. Powers, C. Making sense of social theory , Chapter 16.
• Watts, L. and Hodgson, D. 2019. ‘Power and knowledge’. In. Watts, L. and Hodgson, D. Social justice theory and practice for social work, Chapter 5.
• Cunneen, C. and Tauri, J. 2016. ‘Towards a critical Indigenous criminology.’ In. Cunneen, C. and Tauri, J. Indigenous criminology, pp. 23-43.
• Kim, C.H. and Choi, Y.B. 2017. How meritocracy is defined today – contemporary aspects of meritocracy. Economics and Sociology, 10(1): 112-121.
• Flyvbjerg, B. 2001. ‘Values in social and political inquiry.’ In. Flyvbjerg, B. Making social science matter, Chapter 5.

Other resources:

• Watego, C. 2021.  ‘Who are the real criminals? Making the case for abolishing criminology.’ (YouTube, 1:35:01),
• Anderson, E. 2017. ‘How good social science can and ought to be value-laden’ (YouTube, 17:00) .
• Zigon, J. and Throop, J. 2021. ‘ Phenomenology ‘ Open Encyclopedia of Anthropology .

Introduction to the Social Sciences Copyright © 2023 by The University of Queensland is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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The Craft of Writing a Strong Hypothesis

Table of Contents

Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.

A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.

What is a Hypothesis?

The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .

The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.

The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.

The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.

Different Types of Hypotheses‌

Types of hypotheses

Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.

Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.

1. Null hypothesis

A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.

2. Alternative hypothesis

Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good  alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.

• Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
• Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'

3. Simple hypothesis

A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.

4. Complex hypothesis

In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.

5. Associative and casual hypothesis

Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.

6. Empirical hypothesis

Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.

Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher  the statement after assessing a group of women who take iron tablets and charting the findings.

7. Statistical hypothesis

The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.

Characteristics of a Good Hypothesis

Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:

• A research hypothesis has to be simple yet clear to look justifiable enough.
• It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
• It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
• A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
• If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
• A hypothesis must keep and reflect the scope for further investigations and experiments.

Separating a Hypothesis from a Prediction

Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.

A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.

Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.

For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.

Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.

2. Carry out a recce

Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.

Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.

3. Create a 3-dimensional hypothesis

Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.

In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.

4. Write the first draft

Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.

Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.

5. Proof your hypothesis

After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.

Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.

Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.

Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.

It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.

If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.

2. What is an example of hypothesis?

The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."

3. What is an example of null hypothesis?

A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

• Your hypothesis should be able to predict the relationship and outcome.

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

• Null hypotheses are used to test the claim that "there is no difference between two groups of data".

• Alternative hypotheses test the claim that "there is a difference between two data groups".

7. Difference between research question and research hypothesis?

A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.

8. What is plural for hypothesis?

The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."

9. What is the red queen hypothesis?

The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.

10. Who is known as the father of null hypothesis?

The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.

11. When to reject null hypothesis?

You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.

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Practice  Questions  – Write short note on Importance and Sources of Hypothesis in Sociological Research. [ UPSC 2008]

Approach –  Introduction, What makes Hypothesis relevant in a sociological research?, What are the sources which aids us to derive hypothesis?, Conclusion

INTRODUCTION

A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence.

We know that research begins with a problem or a felt need or difficulty. The purpose of research is to find a solution to the difficulty. It is desirable that the researcher should propose a set of suggested solutions or explanations of the  difficulty which the research proposes to solve. Such tentative solutions formulated as a proposition are called hypotheses. The suggested solutions formulated as hypotheses may or may not be the real solutions to the problem. Whether they are or not is the task of research to test and establish.

DEFINTITIONS

• Lundberg- A Hypothesis is a tentative generalisation, the validity of which remains to be tested. In its most elementary stages, the hypothesis may be any hunch, guess imaginative idea or Intuition whatsoever which becomes the basis of action or Investigation.
• Bogardus- A Hypothesis is a proposition to be tested.
• Goode and Hatt- It is a proposition which can be put to test to determinants validity.
• P. V. Yaung- The idea of ​a temporary but central importance that becomes the basis of useful research is called a working hypothesis.

TYPES OF HYPOTHESIS

i)  Explanatory Hypothesis : The purpose of this hypothesis is to explain a certain fact. All hypotheses are in a way explanatory for a hypothesis is advanced only when we try to explain the observed fact. A large number of hypotheses are advanced to explain the individual facts in life. A theft, a murder, an accident are examples.

ii) Descriptive Hypothesis:  Some times a researcher comes across a complex phenomenon. He/ she does not understand the relations among the observed facts. But how to account for these facts? The answer is a descriptive hypothesis. A hypothesis is descriptive when it is based upon the points of resemblance of some thing. It describes the cause and effect relationship of a phenomenon e.g., the current unemployment rate of a state exceeds 25% of the work force. Similarly, the consumers of local made products constitute asignificant market segment.

iii) Analogical Hypothesis : When we formulate a hypothesis on the basis of similarities (analogy), it is called an analogical hypothesis e.g., families with higher earnings invest more surplus income on long term investments.

iv) Working hypothesis : Some times certain facts cannot be explained adequately by existing hypotheses, and no new hypothesis comes up. Thus, the investigation is held up. In this situation, a researcher formulates a hypothesis which enables to continue investigation. Such a hypothesis, though inadequate and formulated for the purpose of further investigation only, is called a working hypothesis. It is simply accepted as a starting point in the process of investigation.

v) Null Hypothesis:  It is an important concept that is used widely in the sampling theory. It forms the basis of many tests of significance. Under this type, the hypothesis is stated negatively. It is null because it may be nullified, if the evidence of a random sample is unfavourable to the hypothesis. It is a hypothesis being tested (H0). If the calculated value of the test is less than the permissible value, Null hypothesis is accepted, otherwise it is rejected. The rejection of a null hypothesis implies that the difference could not have arisen due to chance or sampling fluctuations.

USES OF HYPOTHESIS

i) It is a starting point for many a research work. ii) It helps in deciding the direction in which to proceed. iii) It helps in selecting and collecting pertinent facts. iv) It is an aid to explanation. v) It helps in drawing specific conclusions. vi) It helps in testing theories. vii) It works as a basis for future knowledge.

ROLE  OF HYPOTHESIS

In any scientific investigation, the role of hypothesis is indispensable as it always guides and gives direction to scientific research. Research remains unfocused without a hypothesis. Without it, the scientist is not in position to decide as to what to observe and how to observe. He may at best beat around the bush. In the words of Northrop, “The function of hypothesis is to direct our search for order among facts, the suggestions formulated in any hypothesis may be solution to the problem, whether they are, is the task of the enquiry”.

First ,  it is an operating tool of theory. It can be deduced from other hypotheses and theories. If it is correctly drawn and scientifically formulated, it enables the researcher to proceed on correct line of study. Due to this progress, the investigator becomes capable of drawing proper conclusions. In the words of Goode and Hatt, “without hypothesis the research is unfocussed, a random empirical wandering. The results cannot be studied as facts with clear meaning. Hypothesis is a necessary link between theory and investigation which leads to discovery and addition to knowledge.

Secondly,  the hypothesis acts as a pointer to enquiry. Scientific research has to proceed in certain definite lines and through hypothesis the researcher becomes capable of knowing specifically what he has to find out by determining the direction provided by the hypothesis. Hypotheses acts like a pole star or a compass to a sailor with the help of which he is able to head in the proper direction.

Thirdly , the hypothesis enables us to select relevant and pertinent facts and makes our task easier. Once, the direction and points are identified, the researcher is in a position to eliminate the irrelevant facts and concentrate only on the relevant facts. Highlighting the role of hypothesis in providing pertinent facts, P.V. Young has stated, “The use of hypothesis prevents a blind research and indiscriminate gathering of masses of data which may later prove irrelevant to the problem under study”. For example, if the researcher is interested in examining the relationship between broken home and juvenile delinquency, he can easily proceed in the proper direction and collect pertinent information succeeded only when he has succeed in formulating a useful hypothesis.

Fourthly , the hypothesis provides guidance by way of providing the direction, pointing to enquiry, enabling to select pertinent facts and helping to draw specific conclusions. It saves the researcher from the botheration of ‘trial and error’ which causes loss of money, energy and time.

Finally,  the hypothesis plays a significant role in facilitating advancement of knowledge beyond one’s value and opinions. In real terms, the science is incomplete without hypotheses.

STAGES OF HYPOTHESIS TESTING

• EXPERIMENTATION   : Research study focuses its study which is manageable and approachable to it and where it can test its hypothesis. The study gradually becomes more focused on its variables and influences on variables so that hypothesis may be tested. In this process, hypothesis can be disproved.
• REHEARSAL TESTING :   The researcher should conduct a pre testing or rehearsal before going for field work or data collection.
• FIELD RESEARCH :  To test and investigate hypothesis, field work with predetermined research methodology tools is conducted in which interviews, observations with stakeholders, questionnaires, surveys etc are used to follow. The documentation study may also happens at this stage.
• PRIMARY & SECONDARY DATA/INFORMATION ANALYSIS :  The primary or secondary data and information’s available prior to hypothesis testing may be used to ascertain validity of hypothesis itself.

Formulating a hypothesis can take place at the very beginning of a research project, or after a bit of research has already been done. Sometimes a researcher knows right from the start which variables she is interested in studying, and she may already have a hunch about their relationships. Other times, a researcher may have an interest in ​a particular topic, trend, or phenomenon, but he may not know enough about it to identify variables or formulate a hypothesis. Whenever a hypothesis is formulated, the most important thing is to be precise about what one’s variables are, what the nature of the relationship between them might be, and how one can go about conducting a study of them.

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Model Answers

Q: Discuss the importance and sources of hypothesis in social research.

Question asked in UPSC Sociology 2020 Paper 1. Download our app for last 20 year question with model answers.

Model Answer:

Importance of Hypothesis in Social Research

Hypothesis in social research refers to a tentative statement or assumption about the relationship between two or more variables. It is a testable prediction that serves as a starting point for conducting a study. Hypotheses are important in social research for several reasons:

1. Direction and focus: Hypotheses provide a clear direction and focus for the research. They help researchers identify the variables that need to be studied and the relationships that need to be explored. For example, a hypothesis might state that “ higher levels of education lead to higher income levels. ” This statement provides a clear direction for the researcher to investigate the relationship between education and income.

2. Basis for research design: Hypotheses serve as the foundation for designing a research study. They help researchers choose the appropriate methods, techniques, and tools to collect and analyze data. For instance, if a researcher wants to test the hypothesis that “ participation in sports reduces the likelihood of engaging in criminal behavior, ” they might design a study that compares crime rates among individuals who participate in sports and those who do not.

3. Testability: Hypotheses are testable statements that can be either supported or refuted by empirical evidence. This testability is crucial for the scientific process, as it allows researchers to build on existing knowledge and contribute to the understanding of social phenomena. For example, if a hypothesis states that “ social media use increases feelings of loneliness, ” researchers can collect data on social media usage and loneliness levels to test this assumption.

4. Explanation and prediction: Hypotheses help researchers explain and predict social phenomena. By identifying relationships between variables, hypotheses can provide insights into the underlying mechanisms and processes that drive social behavior. For instance, a hypothesis that “ unemployment leads to increased crime rates, ” might suggest that addressing unemployment could help reduce crime.

Sources of hypothesis in social research:

1. Theory: Hypotheses can be derived from existing theories in the field. Theories provide a framework for understanding social phenomena and can suggest relationships between variables that can be tested through research. For example, social learning theory might suggest the hypothesis that “ children who witness violence in their homes are more likely to exhibit aggressive behavior. “

2. Previous research: Hypotheses can be based on the findings of previous studies. Researchers can build on existing knowledge by testing new relationships or exploring the same relationships in different contexts. For example, if a previous study found a relationship between poverty and crime in urban areas, a researcher might hypothesize that the same relationship exists in rural areas.

3. Observations and personal experiences: Researchers can develop hypotheses based on their own observations and experiences. These insights can provide a starting point for investigating social phenomena. For example, a researcher who notices a high rate of teenage pregnancy in their community might hypothesize that a lack of access to sexual education is a contributing factor.

4. Expert opinions and literature reviews: Consulting experts in the field and reviewing existing literature can help researchers identify gaps in knowledge and generate hypotheses. For instance, a review of research on the effects of social media on mental health might reveal conflicting findings, leading a researcher to hypothesize that certain factors, such as the type of social media platform or the amount of time spent online, might moderate these effects.

In conclusion, hypotheses play a crucial role in social research by providing direction, focus, and a basis for research design. They are derived from various sources, including theory, previous research, observations, and expert opinions. By testing hypotheses, researchers can contribute to the understanding of social phenomena and inform policies and interventions aimed at addressing social issues.

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QAnon/Pizzagate filmmaker claims Trump said he wants to watch his conspiracy theory movie

Written by Alex Kaplan

Published 04/08/24 12:58 PM EDT

QAnon and Pizzagate conspiracy theorist filmmaker Mike Smith and Mary Flynn O’Neill, the sister of former national security adviser Michael Flynn, claimed that Donald Trump said he wanted to watch Smith’s conspiracy theory movie Into the Light . The claim comes after Trump appeared on stage with Smith at a recent event at Mar-a-Lago that featured a screening of the film and the former president receiving an award from Michael Flynn for supposedly combating human trafficking.

During an April 3 X (formerly Twitter) Space, Smith discussed the Mar-a-Lago event — which was hosted by America’s Future, an organization run by the Flynn family which has become increasingly tied to QAnon — with O’Neill, America’s Future executive director. While hyping Trump’s appearance at the event, O’Neill said that the former president is “supposed to watch that movie. He’s supposed to watch Into the Light ,” and seemed to promise that she would “follow up” with Trump’s staff about it. Smith responded that when Trump was on stage, he said to Smith, “I’m going to watch it.” And when Smith expressed hope that Trump would follow through on his promise, O’Neill said, “Oh, he will.”

Into the Light — the sequel to Smith’s Out of Shadows , which pushed Pizzagate — is described as “a movie made to bring to surface that psychological operations are present and active in today’s society.” The film features fellow QAnon and Pizzagate conspiracy theorist Liz Crokin (another member of America’s Future), and pushes conspiracy theories about the World Economic Forum and the “great reset.”

April 3, 2024

Citation From an April 3, 2024, Twitter/X Space

MIKE SMITH (DIRECTOR, OUT OF SHADOWS AND INTO THE LIGHT ): I told everybody before you came on that you — Gen. Flynn gave President Trump an award for fighting human trafficking, for doing more than anyone — 

MARY FLYNN O’NEILL (EXECUTIVE DIRECTOR, AMERICA’S FUTURE): Children. With children, yeah, that’s right. He's the only president that has ever done anything for human traffic but for children. And it was just a beautiful award. If I had it in front of me, I’d read it to you. But he was really taken by it. He didn’t know it was going to happen, you know, so —

SMITH: Yeah.

O’NEILL: — it was cool. It was really — and it was really cool to see you and Mike and Donald Trump on the stage. It was nice. It was cool.

SMITH: I could — if your brother would not have helped me, I would’ve — I don’t know what I would’ve done because I was literally — I’ll be honest with you. I didn’t expect President Trump to come in, and I’m standing there and I could see him coming in the room and I’m like, what do you say to —

O’NEILL: Yeah

SMITH: — President Trump? I’m like, welcome home?

SMITH: And then, you know, I looked over to your brother and I’m like, “Mike, can you help me?” I was like, you know, God’s done some crazy stuff to me in my life, but that was probably one of the biggest God things ever. Like, that was —

O’NEILL: That was awesome.

SMITH: I was like, I cannot believe this moment. I mean, like how cool is it to just have that moment? I mean, I would — I mean, you can’t —

O’NEILL: Well, it was. It was cool. I’m going to call his secretary, there’s an assistant there, because we also — we gave him one of Gen. Flynn’s bats with a inscription on it. And I’m going to follow up and see because he want — he was supposed to — he’s supposed to watch that movie. He’s supposed to watch Into the Light , so I’m going to follow up and and see if he’s —

SMITH: Well, hopefully, he will. I know he whispered to me — 

O’NEILL: Oh, he will.

SMITH: He said to me, I don’t know if you saw when he left the stage, but he leaned over and he goes, “I guess I — that’s a thank you, and I’m going to watch — I’m going to watch it.”

O’NEILL: I’ll follow up. I’ll follow up.

SMITH: Well, that’d be great.