what is hypothesis in social research

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Developing a Research Question

18 Hypotheses

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

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

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

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

Text Attributions

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

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

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Hypothesis: Functions, Problems, Types, Characteristics, Examples

Basic Elements of the Scientific Method: Hypotheses

The Function of the Hypotheses

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

Problems in Formulating the Hypothesis

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

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

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

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

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

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

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

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

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

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

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

Types of Hypothesis

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

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

Science and Hypothesis

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

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

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

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

The Characteristics for Usable Hypotheses

The criteria for judging a hypothesis as mentioned below:

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

The Conclusion

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

Also Read: Research Methods – Basics

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

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

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Home » What is a Hypothesis – Types, Examples and Writing Guide

What is a Hypothesis – Types, Examples and Writing Guide

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Definition:

Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation.

Hypothesis is often used in scientific research to guide the design of experiments and the collection and analysis of data. It is an essential element of the scientific method, as it allows researchers to make predictions about the outcome of their experiments and to test those predictions to determine their accuracy.

Types of Hypothesis

Types of Hypothesis are as follows:

Research Hypothesis

A research hypothesis is a statement that predicts a relationship between variables. It is usually formulated as a specific statement that can be tested through research, and it is often used in scientific research to guide the design of experiments.

Null Hypothesis

The null hypothesis is a statement that assumes there is no significant difference or relationship between variables. It is often used as a starting point for testing the research hypothesis, and if the results of the study reject the null hypothesis, it suggests that there is a significant difference or relationship between variables.

Alternative Hypothesis

An alternative hypothesis is a statement that assumes there is a significant difference or relationship between variables. It is often used as an alternative to the null hypothesis and is tested against the null hypothesis to determine which statement is more accurate.

Directional Hypothesis

A directional hypothesis is a statement that predicts the direction of the relationship between variables. For example, a researcher might predict that increasing the amount of exercise will result in a decrease in body weight.

Non-directional Hypothesis

A non-directional hypothesis is a statement that predicts the relationship between variables but does not specify the direction. For example, a researcher might predict that there is a relationship between the amount of exercise and body weight, but they do not specify whether increasing or decreasing exercise will affect body weight.

Statistical Hypothesis

A statistical hypothesis is a statement that assumes a particular statistical model or distribution for the data. It is often used in statistical analysis to test the significance of a particular result.

Composite Hypothesis

A composite hypothesis is a statement that assumes more than one condition or outcome. It can be divided into several sub-hypotheses, each of which represents a different possible outcome.

Empirical Hypothesis

An empirical hypothesis is a statement that is based on observed phenomena or data. It is often used in scientific research to develop theories or models that explain the observed phenomena.

Simple Hypothesis

A simple hypothesis is a statement that assumes only one outcome or condition. It is often used in scientific research to test a single variable or factor.

Complex Hypothesis

A complex hypothesis is a statement that assumes multiple outcomes or conditions. It is often used in scientific research to test the effects of multiple variables or factors on a particular outcome.

Applications of Hypothesis

Hypotheses are used in various fields to guide research and make predictions about the outcomes of experiments or observations. Here are some examples of how hypotheses are applied in different fields:

• Science : In scientific research, hypotheses are used to test the validity of theories and models that explain natural phenomena. For example, a hypothesis might be formulated to test the effects of a particular variable on a natural system, such as the effects of climate change on an ecosystem.
• Medicine : In medical research, hypotheses are used to test the effectiveness of treatments and therapies for specific conditions. For example, a hypothesis might be formulated to test the effects of a new drug on a particular disease.
• Psychology : In psychology, hypotheses are used to test theories and models of human behavior and cognition. For example, a hypothesis might be formulated to test the effects of a particular stimulus on the brain or behavior.
• Sociology : In sociology, hypotheses are used to test theories and models of social phenomena, such as the effects of social structures or institutions on human behavior. For example, a hypothesis might be formulated to test the effects of income inequality on crime rates.
• Business : In business research, hypotheses are used to test the validity of theories and models that explain business phenomena, such as consumer behavior or market trends. For example, a hypothesis might be formulated to test the effects of a new marketing campaign on consumer buying behavior.
• Engineering : In engineering, hypotheses are used to test the effectiveness of new technologies or designs. For example, a hypothesis might be formulated to test the efficiency of a new solar panel design.

How to write a Hypothesis

Here are the steps to follow when writing a hypothesis:

Identify the Research Question

The first step is to identify the research question that you want to answer through your study. This question should be clear, specific, and focused. It should be something that can be investigated empirically and that has some relevance or significance in the field.

Conduct a Literature Review

Before writing your hypothesis, it’s essential to conduct a thorough literature review to understand what is already known about the topic. This will help you to identify the research gap and formulate a hypothesis that builds on existing knowledge.

Determine the Variables

The next step is to identify the variables involved in the research question. A variable is any characteristic or factor that can vary or change. There are two types of variables: independent and dependent. The independent variable is the one that is manipulated or changed by the researcher, while the dependent variable is the one that is measured or observed as a result of the independent variable.

Formulate the Hypothesis

Based on the research question and the variables involved, you can now formulate your hypothesis. A hypothesis should be a clear and concise statement that predicts the relationship between the variables. It should be testable through empirical research and based on existing theory or evidence.

Write the Null Hypothesis

The null hypothesis is the opposite of the alternative hypothesis, which is the hypothesis that you are testing. The null hypothesis states that there is no significant difference or relationship between the variables. It is important to write the null hypothesis because it allows you to compare your results with what would be expected by chance.

Refine the Hypothesis

After formulating the hypothesis, it’s important to refine it and make it more precise. This may involve clarifying the variables, specifying the direction of the relationship, or making the hypothesis more testable.

Examples of Hypothesis

Here are a few examples of hypotheses in different fields:

• Psychology : “Increased exposure to violent video games leads to increased aggressive behavior in adolescents.”
• Biology : “Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.”
• Sociology : “Individuals who grow up in households with higher socioeconomic status will have higher levels of education and income as adults.”
• Education : “Implementing a new teaching method will result in higher student achievement scores.”
• Marketing : “Customers who receive a personalized email will be more likely to make a purchase than those who receive a generic email.”
• Physics : “An increase in temperature will cause an increase in the volume of a gas, assuming all other variables remain constant.”
• Medicine : “Consuming a diet high in saturated fats will increase the risk of developing heart disease.”

Purpose of Hypothesis

The purpose of a hypothesis is to provide a testable explanation for an observed phenomenon or a prediction of a future outcome based on existing knowledge or theories. A hypothesis is an essential part of the scientific method and helps to guide the research process by providing a clear focus for investigation. It enables scientists to design experiments or studies to gather evidence and data that can support or refute the proposed explanation or prediction.

The formulation of a hypothesis is based on existing knowledge, observations, and theories, and it should be specific, testable, and falsifiable. A specific hypothesis helps to define the research question, which is important in the research process as it guides the selection of an appropriate research design and methodology. Testability of the hypothesis means that it can be proven or disproven through empirical data collection and analysis. Falsifiability means that the hypothesis should be formulated in such a way that it can be proven wrong if it is incorrect.

In addition to guiding the research process, the testing of hypotheses can lead to new discoveries and advancements in scientific knowledge. When a hypothesis is supported by the data, it can be used to develop new theories or models to explain the observed phenomenon. When a hypothesis is not supported by the data, it can help to refine existing theories or prompt the development of new hypotheses to explain the phenomenon.

When to use Hypothesis

Here are some common situations in which hypotheses are used:

• In scientific research , hypotheses are used to guide the design of experiments and to help researchers make predictions about the outcomes of those experiments.
• In social science research , hypotheses are used to test theories about human behavior, social relationships, and other phenomena.
• I n business , hypotheses can be used to guide decisions about marketing, product development, and other areas. For example, a hypothesis might be that a new product will sell well in a particular market, and this hypothesis can be tested through market research.

Characteristics of Hypothesis

Here are some common characteristics of a hypothesis:

• Testable : A hypothesis must be able to be tested through observation or experimentation. This means that it must be possible to collect data that will either support or refute the hypothesis.
• Falsifiable : A hypothesis must be able to be proven false if it is not supported by the data. If a hypothesis cannot be falsified, then it is not a scientific hypothesis.
• Clear and concise : A hypothesis should be stated in a clear and concise manner so that it can be easily understood and tested.
• Based on existing knowledge : A hypothesis should be based on existing knowledge and research in the field. It should not be based on personal beliefs or opinions.
• Specific : A hypothesis should be specific in terms of the variables being tested and the predicted outcome. This will help to ensure that the research is focused and well-designed.
• Tentative: A hypothesis is a tentative statement or assumption that requires further testing and evidence to be confirmed or refuted. It is not a final conclusion or assertion.
• Relevant : A hypothesis should be relevant to the research question or problem being studied. It should address a gap in knowledge or provide a new perspective on the issue.

Advantages of Hypothesis

Hypotheses have several advantages in scientific research and experimentation:

• Guides research: A hypothesis provides a clear and specific direction for research. It helps to focus the research question, select appropriate methods and variables, and interpret the results.
• Predictive powe r: A hypothesis makes predictions about the outcome of research, which can be tested through experimentation. This allows researchers to evaluate the validity of the hypothesis and make new discoveries.
• Facilitates communication: A hypothesis provides a common language and framework for scientists to communicate with one another about their research. This helps to facilitate the exchange of ideas and promotes collaboration.
• Efficient use of resources: A hypothesis helps researchers to use their time, resources, and funding efficiently by directing them towards specific research questions and methods that are most likely to yield results.
• Provides a basis for further research: A hypothesis that is supported by data provides a basis for further research and exploration. It can lead to new hypotheses, theories, and discoveries.
• Increases objectivity: A hypothesis can help to increase objectivity in research by providing a clear and specific framework for testing and interpreting results. This can reduce bias and increase the reliability of research findings.

Limitations of Hypothesis

Some Limitations of the Hypothesis are as follows:

• Limited to observable phenomena: Hypotheses are limited to observable phenomena and cannot account for unobservable or intangible factors. This means that some research questions may not be amenable to hypothesis testing.
• May be inaccurate or incomplete: Hypotheses are based on existing knowledge and research, which may be incomplete or inaccurate. This can lead to flawed hypotheses and erroneous conclusions.
• May be biased: Hypotheses may be biased by the researcher’s own beliefs, values, or assumptions. This can lead to selective interpretation of data and a lack of objectivity in research.
• Cannot prove causation: A hypothesis can only show a correlation between variables, but it cannot prove causation. This requires further experimentation and analysis.
• Limited to specific contexts: Hypotheses are limited to specific contexts and may not be generalizable to other situations or populations. This means that results may not be applicable in other contexts or may require further testing.
• May be affected by chance : Hypotheses may be affected by chance or random variation, which can obscure or distort the true relationship between variables.

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• What is Hypothesis
• Meaning of Hypothesis

Characteristics of Hypothesis

• Sources of Hypothesis
• Types of Hypotheses
• Role of Hypothesis in Social Research  

Introduction

The concept of a hypothesis holds significant importance within the realm of research, serving as a foundational element in the investigative process. It acts as a proposed explanation or assumption that undergoes empirical scrutiny during research endeavours. Essentially, the role of a hypothesis is to suggest new avenues of experimentation and observation, offering a guiding principle for research endeavours.

Defined as a proposition or a set of propositions aimed at explaining a specific set of phenomena, a hypothesis serves as a provisional conjecture directing an investigation or is accepted as highly probable based on existing evidence. It commonly takes the form of a predictive statement, facilitating testability through scientific methodologies involving independent and dependent variables.

For example, consider the following hypotheses:

(i) Students enrolled in tuition programs exhibit superior academic performance compared to those without tuition. (ii) There is no significant difference in academic performance between female and male students.

These statements represent hypotheses that are amenable to objective verification and empirical testing, illustrating the fundamental purpose of a hypothesis in delineating research objectives and facilitating empirical validation.

There are two interpretations of the term “hypothesis”:

The first interpretation suggests that the word “hypothesis” originates from the fusion of two Greek terms, “hypo” and “thesis.” “Hypo” denotes “under,” while “thesis” pertains to a proposition or statement. Consequently, a hypothesis is regarded as any proposition under consideration.

The second interpretation views the term “hypothesis” as a compound of “hypo” and “thesis” as well. Here, “hypo” signifies “less than,” while “thesis” refers to a commonly accepted notion or viewpoint.

Combining these perspectives, a hypothesis suggests a perspective that diverges from the conventional understanding, indicating a more constrained viewpoint. It denotes a departure from generalizations and serves as a pivotal element in the process of scientific inquiry, marking the transition from basic inquiry to a structured scientific endeavour.

Conclusion: Based on the definitions provided earlier, it can be argued that a hypothesis functions as an initial explanation for a research issue, a potential result of the research, or an educated guess regarding the research findings. It establishes a link between multiple variables, with the aim of testing and offering appropriate direction for further clarification in the research process. Clearly, a hypothesis represents a temporary proposition, offering a tentative solution to the scientific problem under investigation. Put simply, a hypothesis is a formal declaration describing the expected connection between an independent and dependent variable. It’s worth noting that a research question essentially mirrors a hypothesis but is framed as an inquiry, providing a provisional forecast about the relationship between two or more variables.

      The researcher begins the investigative journey by assuming a potential solution to a specific issue and holding a personal belief in its accuracy. George A. Lundberg emphasizes that when gathering data using a hypothesis, it’s crucial to recognize the inherent limitations of our senses. This involves taking steps to reduce error by narrowing the focus of investigation, avoiding excessive attention on aspects deemed unimportant based on previous knowledge. Hypotheses should possess certain characteristic traits, including:

      1. Conceptual Clarity: A well-constructed hypothesis requires conceptual clarity. This means offering precise and widely acknowledged definitions for the pertinent concepts, steering clear of subjective interpretations. It’s recommended to articulate and elucidate these concepts in the research framework using universally comprehensible and communicable language. Engaging in discussions with peers and methodically resolving any areas needing clarification can greatly improve the overall conceptual clarity.

      2. Hypothesis should be Capable of being Tested: To prepare a hypothesis for examination, a researcher must ensure it’s capable of being tested. This requires initial inquiries to confirm its testability. A hypothesis is deemed testable if it permits the formulation of predictions that can be confirmed or refuted through observation, and it should establish a clear link between variables. Additionally, it’s essential for a hypothesis to be feasible for testing within a reasonable period. Even if a hypothesis seems exceptional, if it can’t be tested promptly, it’s not suitable for use. Furthermore, it’s vital to articulate the explanatory aim of the hypothesis clearly.

      3. It Should have Empirical Referents: A credible hypothesis should be based on observable data rather than moral evaluations. Its elements should accurately reflect empirical facts, and any elements influenced by personal opinions should be thoroughly examined.

      4. Easily Understandable: The hypothesis should be straightforward and easy to understand. It’s best to use plain language to communicate the idea, as mistakenly believing that using complex terms makes the hypothesis more important is incorrect. In truth, using complicated technical jargon doesn’t make the hypothesis more valuable. Also, whenever possible, the hypothesis should be consistent with established facts.

      5. It must be Specific: A hypothesis needs to be clearly articulated, detailing all the operations and predictions it encompasses. Although lofty concepts may appear impressive, it’s vital to make hypotheses precise by explicitly outlining the operations and predictions involved. Achieving specificity requires including specific indicators that directly address the research questions, such as political office, occupation, effective income, and education. These indicators not only improve the usability of the hypothesis but also bolster the practicality, significance, and validity of the research. To steer clear of selective evidence pitfalls, scientific predictions and hypotheses should aim to be as concrete and specific as they can be.

      6. It Should be Related to Available Techniques: A hypothesis should align with established techniques and theories without contradiction. Crafting insightful questions necessitates familiarity with the methods available for hypothesis testing. While recognizing that modern hypotheses can pose challenges for existing techniques, their relevance to available methods remains crucial for utility. This doesn’t rule out the development of hypotheses in the absence of knowledge about specific techniques; instead, it hinges on the chosen research design and methodology.

      7. Relation with the Body of Theory: Usually, a student might be driven to delve into an intriguing subject without considering whether their research adds to the debate surrounding established theories of social relations. Advancement in any field depends on the accumulation of knowledge and theories; it cannot progress if each study remains disconnected. As emphasized by Goode and Hatt, the value of data obtained from your hypothesis source lies in its logical derivation and alignment with a set of sociological propositions, irrespective of the source’s origin.

      8. It Should be the Closest to things Observable: The essence of formulating a hypothesis lies in its direct connection to observable phenomena. Without this link, verifying its alignment with empirical evidence becomes unfeasible. An effective hypothesis should pave the way for deriving deductions. As stated by Morris Raphael Cohen and Ernest Nagel, a hypothesis should be structured to enable deductions, aiding in assessing its explanatory power regarding the observed facts.

      9. Hypothesis Should be Simple and Brief: A well-crafted hypothesis ought to be clear and succinct. Its simplicity aids not only the researcher but also the research process. By keeping it brief, it becomes easier to observe and analyze. Articulating the hypothesis in scientific language enhances its clarity and assists in better understanding the underlying ideas and significance.

      Conclusion: The description above underscores the critical importance of precision and clarity in formulating hypotheses. When a hypothesis lacks these qualities, the conclusions drawn from it may be unreliable. Furthermore, a hypothesis should be capable of being tested, as emphasized by Kothari, who suggests that hypotheses can be tested by exploring other deductions that stem from them and can be confirmed or disproved through observation. Simplifying the language used to express a hypothesis is crucial to ensure comprehension by all parties involved. Ultimately, a hypothesis should be coherent, grounded in established facts, and consistent with existing knowledge. Breaking down a hypothesis into sub-hypotheses based on its relevance to the research problem can enhance specificity. Utilizing hypotheses in drawing conclusions serves to make the research process more precise, manageable, and scientific.

Sources of Hypotheses

Hypotheses can originate from diverse origins. Below are outlined several primary sources for hypotheses:

1. Scientific Conceptual History: The evolution of scientific pursuits highlights how a scientist’s personal experiences profoundly shape the inquiries they raise and the potential solutions they propose. Each scientist tends to identify captivating patterns within seemingly ordinary data, drawing on their unique life journey. Over time, countless breakthroughs have emerged when an individual with the right perspective makes a relevant observation, guided by their distinct background and encounters. Personal narratives wield significant influence in moulding one’s perspective and thought process, steering them towards particular hypotheses.

2. Analogies: Analogies frequently provide fertile ground for generating valuable hypotheses. Students of sociology and political science often encounter analogies throughout their academic pursuits that liken society and the state to various phenomena—be it a biological organism, the application of natural law to social dynamics, or drawing parallels between thermodynamics and social systems. While recognizing the limitations inherent in analogies, they nonetheless offer insightful perspectives that can spark and guide inquiries when formulated as hypotheses. As these hypotheses undergo validation through empirical observation, they contribute to the introduction of new concepts. For instance, the incorporation of the concept of segregation from plant ecology into sociology has significantly enriched sociological theory. Numerous similar instances highlight the suggestive nature of analogies. Nonetheless, it’s crucial to exercise caution to avoid blindly adopting models from other disciplines. Thorough scrutiny of concepts and assessment of their applicability within the new framework are imperative before their adoption.

3. Based on Findings of Earlier Researchers: Researchers often draw inspiration from prior studies conducted by their peers when formulating hypotheses. By extending upon earlier findings, researchers may suggest that similar relationships between certain variables exist in their own study. This practice is common among researchers seeking to replicate studies conducted in different contexts or settings. In social science, many studies are exploratory, beginning without predefined hypotheses. As a result, the discoveries from these studies may serve as hypotheses for subsequent, more rigorous investigations aimed at testing specific hypotheses.

4. Theoretical and Logical Deductions: A hypothesis often emerges from a well-established theoretical framework, proposing specific outcomes through logical inference given particular circumstances. This framework embodies existing knowledge, and the resulting hypotheses are deemed credible if the framework remains valid. It’s important to recognize that the seemingly divergent methods of hypothesis formulation—empirical observations and theoretical constructs—actually lie along a spectrum. Hypotheses occupy a middle ground on this spectrum, serving as a link between empirical evidence and theoretical frameworks. Both approaches, as illustrated by the empirical focus of the Chicago School in American Sociology and the theoretical emphasis of the Mertonian and Parsonian approach, have proven effective. Essentially, hypotheses can be inferred from theoretical models, highlighting the interplay between empirical observations and theoretical underpinnings in hypothesis development.

5. Culture Based Value Orientation: Acknowledging the influence of cultural values on the development of scientific disciplines is paramount. The prevailing cultural norms in a given environment can significantly shape the core hypotheses within a discipline. William J. Goode and Paul K. Hatt highlight how the strong emphasis on personal happiness in American culture has profoundly impacted social science in the United States. This emphasis has led to an extensive exploration of personal happiness across various branches of social science, examining its relationship with factors like income, education, occupation, and social class. Cultural values not only influence the selection of hypotheses by researchers but also contribute to the emergence of certain ideas within specific societies or cultures. Furthermore, the collective wisdom ingrained in a culture can inspire new hypotheses. In essence, as Larrabee suggests, the most fruitful hypotheses often stem from a blend of past experiences and imaginative thinking within the scientific community.

Types of Hypothesis

Before embarking on their research journey, scientists are tasked with formulating a research hypothesis, a vital component within the scientific method. This pivotal step significantly influences the direction and outcome of the study. It entails a comprehensive review of relevant literature in the field and the meticulous selection of an experimental framework conducive to gathering data for either confirming or challenging the proposed hypothesis. These hypotheses can manifest in various forms:

1. Simple Hypothesis: A simple hypothesis outlines a relationship between two variables: the independent and dependent variables. For instance:

• Increased unemployment correlates with elevated crime rates in society.
• Reduced fertilizer usage correlates with decreased agricultural productivity.
• Greater poverty within a society corresponds with higher crime rates.

2. Complex Hypothesis: A complex hypothesis demonstrates interconnections among multiple variables. For instance:

• In a society where poverty is higher, the illiteracy rate tends to increase, leading to a rise in crime rates (three variables: two independent variables and one dependent variable).
• Reduced usage of fertilizers, improved seeds, and modern equipment correlates with lower agricultural productivity (four variables: three independent variables and one dependent variable).
• Elevated illiteracy rates within a society often correspond with increased poverty levels and crime rates (three variables: one independent variable and two dependent variables).

3. Alternative Hypothesis: The alternative hypothesis usually mirrors the researcher’s aim to establish a certain effect, whereas the null hypothesis is crafted with the intent of being refuted. Thus, researchers aim to challenge and reject the null hypothesis, while the alternative hypothesis encompasses various alternative scenarios. Rejecting a true hypothesis carries substantial consequences, especially concerning the null hypothesis, where the likelihood of rejection, when the hypothesis is actually true, is denoted as alpha (the selected significance level), often maintained at a low threshold. It’s crucial for the null hypothesis to be precise, steering clear of vague or ambiguous assertions regarding a specific value.

4. Working Hypothesis: A working hypothesis is an initial proposition adopted tentatively to guide further research, aiming to potentially contribute to the formation of a viable theory, even if the hypothesis isn’t ultimately proven correct. Like any hypothesis, a working one is crafted as a set of expected outcomes, typically aligned with the goals of exploratory research in practical investigations. Particularly in qualitative research, working hypotheses are often used as a conceptual framework. Their provisional nature makes them useful as organizational aids in applied research, providing guidance for tackling nascent problems.

5. Null Hypothesis: This describes the conventional approach to crafting a hypothesis. It involves suggesting that there’s no connection between two groups under study based on a specific factor. It might also propose that there’s no significant difference when comparing various groups concerning a particular factor. For example, a null hypothesis could state: “There’s no observable gap in the academic performance of high school students who participate in extracurricular activities compared to those who don’t.” Often, the null hypothesis is used to allow experimental results to challenge the hypothesis and demonstrate a clear correlation. For instance:

• Poverty isn’t linked to the crime rate in society.
• Illiteracy isn’t linked to the unemployment rate in society.

The null hypothesis serves a distinct purpose, formulated to be disproved or rejected to establish a connection between variables. Usually, researchers develop a null hypothesis with the intention of proving it false to confirm the existence of a relationship between variables, denoted by H O .

6. Logical Hypothesis: A logical hypothesis entails propositions that can be logically validated. These hypotheses elucidate connections that can be logically reasoned and are supported by logical evidence. While logical validation doesn’t preclude statistical confirmation, it underscores the capacity to substantiate the hypothesis through logical deduction.

7. Statistical Hypothesis: A statistical hypothesis is a research question that can be supported by statistical evidence. It’s distinguished by its potential for validation through statistical methods. In essence, it suggests that any research inquiry utilizing quantitative approaches to generate and assess statistical data capable of validation falls under the category of a statistical hypothesis. Moreover, it’s important to highlight that the components of a statistical hypothesis can be broken down into quantifiable sub-variables for statistical examination.

8. Causal Hypothesis: Multiple investigations focus on evaluating how one factor impacts another by gauging their level of influence. In these scenarios, researchers create hypotheses to articulate the potential effects of changes in a specific variable on another. These hypotheses, known as bi-variate causal hypotheses, outline the relationship between two components: the cause and the effect. For instance, a causal hypothesis might propose that “High school students who participate in extracurricular activities allocate less time to studying, resulting in a lower GPA.” Researchers validate such hypotheses by employing statistical methodologies to establish a connection between the cause and the effect. Moreover, they must account for and eliminate the possibility that factors other than those under scrutiny are accountable for the observed outcomes.

9. Scientific Hypothesis: A typical approach to addressing a problem is often referred to as a hypothesis, described as an “informed guess” because it relies on evidence. However, some scientists argue against labeling it as a “guess,” considering it misleading. Researchers may evaluate and discard several hypotheses before reaching a solution to the problem.

Conclusion : Based on the previous explanation, it can be argued that hypotheses manifest in various forms, depending on the nature and objectives of the research. The selection of a hypothesis is heavily influenced by the specific characteristics of the study in question. Recently, scholars in the field of philosophy of science have endeavored to integrate different methodologies for assessing hypotheses and the scientific process overall. This initiative seeks to develop a cohesive framework that accommodates the unique aspects of each methodology. Given that hypotheses are temporary assertions open to confirmation or rejection, they demand significant scrutiny, coupled with a deep understanding of scientific principles and the utilization of statistical techniques to explore phenomena.

Role of Hypothesis in Social Research

In scientific inquiry, the hypothesis serves as a cornerstone, providing essential guidance and structure throughout the research process. Without a hypothesis, the investigation lacks a focal point, leaving researchers adrift without a clear framework for observation and methodology. Northrop emphasizes the pivotal role of the hypothesis in guiding the quest for patterns within data, offering potential avenues for resolving the research question at hand. The verification of these suggestions becomes the primary aim of the inquiry.

The deductive formulation of a hypothesis leads to various outcomes. As experiments are carried out to test its validity, a plethora of new insights emerge, enriching the scientist’s comprehension of the subject matter. Despite the potential for a hypothesis to be disproven, its rejection isn’t without merit. There exist at least five compelling justifications for the indispensable role of the hypothesis as a fundamental tool in scientific inquiry. A thorough elucidation of these rationales follows:

1. Operating Tool of Theory: Extracting insights from alternative hypotheses and theories is feasible. When crafted precisely and rooted in scientific fundamentals, a hypothesis provides researchers with a structured avenue for inquiry. This progression facilitates the extraction of significant insights. According to Goode and Hatt, the absence of a hypothesis leads to aimless research, marked by haphazard empirical investigations. Consequently, the findings lack coherence and substantive analysis. A hypothesis acts as a vital link between theory and exploration, nurturing discovery and enriching our understanding.

2. Pointer of Enquiry: A hypothesis acts as a navigational tool in research endeavors, offering a clear direction for investigation. Similar to how a pole star guides a sailor or a compass points the way, a hypothesis provides researchers with the necessary structure to explore specific avenues effectively in scientific inquiry.

3. Capable to Make Research Process Easy: The development of a hypothesis serves to streamline the research process by aiding in the identification of pertinent information, thus simplifying the task at hand. By establishing clear directions and focal points, researchers can sift through data more efficiently, disregarding extraneous details. P.V. Young underscores the importance of hypotheses in preventing aimless data collection, which might otherwise overwhelm the study. For instance, in examining the link between broken homes and juvenile delinquency, a well-crafted hypothesis directs researchers and ensures the acquisition of relevant data. Therefore, the efficacy of research largely depends on the formulation of a concise and purposeful hypothesis.

4. Guide of the Researcher: A hypothesis serves as a compass, guiding researchers towards a path of inquiry, aiding in the identification of pertinent data, and enabling the development of precise conclusions. It shields researchers from the pitfalls of aimless experimentation, thereby sparing them from potential financial, energetic, and temporal losses.

5. It Work as Facilitator: Hypotheses play a pivotal role in advancing knowledge beyond personal beliefs and viewpoints. Science fundamentally relies on hypotheses to reach completion and validity.

Conclusion: Based on the preceding description, it’s crucial to acknowledge the pivotal role hypotheses play in steering towards valid conjectures. Even if a hypothesis is incorrect, it can still offer valuable insights into the investigative path. Cohen and Nagel underscore the indispensability of hypotheses at every juncture of scientific inquiry. It’s imperative to recognize that the application of overarching principles or laws in an ongoing investigation carries inherent risk, as they may not always be directly applicable. These general laws of any scientific field essentially function as hypotheses, guiding the inquiry across all its phases. Thus, it can be asserted that hypotheses have held significant sway in scientific research throughout history, spanning from primitive times to the contemporary era.

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What is qualitative secondary analysis? How can it be most effectively applied in social research? This timely and accomplished book offers readers a well informed, reliable guide to all aspects of qualitative secondary analysis. The book: Defines secondary analysis. Distinguishes between quantitative and qualitative secondary analysis. Maps the main types of qualitative secondary analysis. Covers the key ethical and legal issues. Offers a practical guide to effective research. Sets the agenda for future developments in the subject. Written by an experienced researcher and teacher with a background in sociology, the book is a comprehensive and invaluable introduction to this growing field of social research.

• By: Geoff Payne & Judy Payne
• In: Key Concepts in Social Research
• Chapter DOI: https:// doi. org/10.4135/9781849209397.n23
• Subject: Anthropology , Business and Management , Criminology and Criminal Justice , Communication and Media Studies , Counseling and Psychotherapy , Economics , Education , Geography , Health , History , Marketing , Nursing , Political Science and International Relations , Psychology , Social Policy and Public Policy , Social Work , Sociology
• Keywords: cell phones ; ownership ; students
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A hypothesis is a reasoned but provisional supposition about the relationship between two or more social phenomena, stated in terms that can be empirically tested and which forms the focus for research, particularly in quantitative studies .

Section Outline: Preliminaries to research, and ‘anticipations’. Working hypotheses as a starting point. Example: student phone ownership. Evolving descriptive and relational hypotheses. Direction of relationship and theoretical models. Example: social mobility. Format of hypotheses in quantitative methods: statement; about single relationship or phenomenon; clearly expressed; empirically testable. Format of hypotheses in qualitative methods: less specific ‘propositions’; discovered from data; limited applicability. Confirmation, proof and disproof. The ‘null hypothesis’. ‘Rejecting’ the null hypothesis .

In research, we work from ‘knowing less’ towards ‘knowing more’. We do not collect data without prior information or reflection. We decide what we want to know about; how much is already known about it; the varieties of form it might present; where it can be studied; how we might best collect information about it; and how we intend to analyse data once they have been collected. While researchers do not exclusively seek those findings that support their prior ideas, they have at least implicit anticipations about what they might find. It is in this area of ‘anticipation’ that we encounter the hypothesis.

A hypothesis is a tentative suggestion about what we might find. At its simplest, it takes the form that ‘something is happening’. For example, from general observation on campus, we might guess that ‘a lot of students own mobile phones’. Our research task following from such a general hypothesis would be to collect trustworthy information so that we could confidently report phone ownership rates.

What we have here is a ‘working hypothesis’, a statement that is imprecise, but which expresses the research's main direction. Its [Page 113] usefulness is providing a starting point from which more precise hypotheses can be developed, and to help in designing the research. It narrows the topic (student phone ownership is about phones , and students , not about, or say, TV and elderly people). It may suggest extra ideas, like whether male and female students have the same level of ownership, or use them for the same purposes, and is best understood as a stage in the research process (Kumar 1999: 64–70).

Working hypotheses differ from the more conventional use of the term, particularly in quantitative research, to mean a more precise statement about descriptive or relational phenomena. By ‘descriptive hypotheses ‘, we mean statements about events, i.e. that something is happening, or happening at a certain rate. In our example, ‘a lot of students’ could be made more precise by rephrasing it as ‘85 per cent of undergraduates’. Our fact-gathering exercise would become more focused.

‘Relational hypotheses ‘, on the other hand, express the anticipation that two or more items in the research will be related to one another in a particular way. The hypothesis that ‘female ownership rates are higher than male ones’ relates the variable ‘gender’ to the variable ‘phone ownership’. It relates the variables in two specific ways. First it plausibly assumes gender behaviour determines phone usage, rather than the reverse. The relationship has a direction. Second, it posits that female gender behaviour leads to greater ownership, not less. Whereas a descriptive hypothesis leads to simple exploration, or fact-gathering, a relational hypothesis points towards investigating a more complex set of things, their interconnection, and a theoretical model that explains why there is that interconnection.

The student phone example was drawn from casual observation, but most relational hypotheses are derived from findings or theoretical models from previous studies. For example, a social mobility study might hypothesise from Marx's class theory that ‘sons are likely to become members of the same class as their fathers’. This because under Marx's idea of capitalism, the upper class have more material assets to assist their children than do the working class. Equally, the same hypothesis could draw on the previous findings of Glass's 1949 pioneering British mobility study, that about two-thirds of ‘service class’ men had fathers from that class (Rose 1982; Schutt 1999: 38–42).

Thus in quantitative research, a hypothesis has four main characteristics:

• It is expressed as a statement, not a question (though it may answer an implicit question): ‘85 per cent of students own mobile phones’, not ‘Do 85 per cent of students own mobile phones?’.
• It addresses a single phenomenon, or a single relation between phenomena.
• It is stated clearly and is logically consistent.
• And most important of all it is empirically testable (‘God is Great’ is not a hypothesis).

In qualitative research (Qualitative Methods) , hypotheses are rarely stated at the outset. This is because most qualitative researchers believe social behaviour is complex and transitory, and does not consist of constant regularities. Human actions therefore do not follow ‘laws’. They see relational hypotheses as falsely implying that we can discover law-like patterns that predetermine action. Furthermore, adopting a hypothesis at an early stage can restrict the scope of enquiry, and not reflect the realities of the research setting. Because relational hypotheses connect ‘variables’, this arbitrarily isolates one part of people's lives from their context, doing violence to the ‘true’ nature of context-specific events and human experience.

This does not mean that qualitative researchers never use hypotheses. They too start with theories and findings, operationalise their concepts, and have anticipations. However, they favour looser, descriptive hypotheses; using the term ‘hypothesis’ less, and sometimes preferring the word ‘proposition’ (Strauss and Corbin 1998: 102). They restrict any hypothesis or proposition to a specific social situation, and avoid statistical techniques for evaluating their interpretations. Perhaps most important of all, they engage with their data in order to discover their preliminary hypotheses, and refine them by further data collection (Grounded Theory) . The hypothesis emerges progressively from the data, rather than the hypothesis determining from the outset what data are collected .

In quantitative research, the operational measurements we make cannot logically prove that a relationship exists as hypothesised (Positivism and Realism) . Our limited empirical activities can never establish that a relation holds true for all situations at all times, although we can find supporting evidence that helps to confirm it. In practice, we work the other way around, seeing if something is untrue . If we find a single case that goes contrary to our hypothesis, that is a sufficient disproof: we would have to modify or abandon our hypothesis.

For this reason, statistical analysis often works with a special kind of hypothesis. Up to this point we have talked about hypotheses as general theoretical statements about relationships between factors. In statistical work, the term ‘hypothesis’ is more precise, indicating a numerically measurable association which can be ‘tested’, and normally referred to as ‘the null hypothesis’.

[Page 115] This takes the form of stating the reverse of the more theoretical one with which we started. So ‘female ownership rates are higher than male ones’ yields the null hypothesis that ‘there is no difference between male and female phone ownership rates’. If we do then find a difference, we can ‘reject the null hypothesis’ (an introduction to the statistical treatment of this process can be found in most statistics textbooks: a particularly clear one is to be found in Rose and Sullivan 1993).

In rejecting the null hypothesis, we will have established a disproof of it (which as we noted before, we can legitimately do, whereas we could not logically prove something]. If we disprove the null hypothesis, that leaves us with our original hypothesis: we do not unquestioningly ‘accept’ it, but we have increased the chances that it is right. In our phone ownership example, we might have shown that ownership rates differ, but not that they differ in the anticipated way, or that outside of our study, ownership rates always differ in the way we seem to have found. Of course, we cannot prove that absolutely.

If our hypothesis takes the general form of ‘A is greater than B’ (‘female ownership rates are higher than male ones’), then the null hypothesis usually takes the form of ‘There is no difference between A and B’ (‘there is no difference between male and female phone ownership rates’). In fact, we might find that what disproves our null hypothesis is evidence that not only shows a difference, but a difference showing male rates are actually higher than female rates. This would also be a disproof of our hypothesis.

We must set our empirical tests carefully. If we are too generous, we might confirm our original hypothesis when it is actually wrong (we would be accepting evidence to disprove the null hypothesis when it is insufficient). If we are too rigorous, we might mistakenly reject a basically valid hypothesis (we would in fact find enough support for the null hypothesis not to reject it). The mathematical methods for balancing these problems are covered in all introductory statistics texts.

• descriptive hypothesis
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• Grounded Theory
• Positivism and Realism
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What Is A Research Hypothesis?

A Plain-Language Explainer + Practical Examples

Research Hypothesis 101

• What is a hypothesis ?
• What is a research hypothesis (scientific hypothesis)?
• Requirements for a research hypothesis
• Definition of a research hypothesis
• The null hypothesis

What is a hypothesis?

Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:

Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.

In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:

Hypothesis: sleep impacts academic performance.

This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.

But that’s not good enough…

Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .

What is a research hypothesis?

A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .

Let’s take a look at these more closely.

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Hypothesis Essential #1: Specificity & Clarity

A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).

Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.

Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.

As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.

Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.

Hypothesis Essential #2: Testability (Provability)

A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.

For example, consider the hypothesis we mentioned earlier:

We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference.

Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?

So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂

Defining A Research Hypothesis

You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.

A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.

So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.

What about the null hypothesis?

You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.

For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.

At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.

And there you have it – hypotheses in a nutshell. 

If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.

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18 Comments

Very useful information. I benefit more from getting more information in this regard.

Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc

In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin

This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.

Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?

It’s a counter-proposal to be proven as a rejection

Please what is the difference between alternate hypothesis and research hypothesis?

It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?

In qualitative research, one typically uses propositions, not hypotheses.

could you please elaborate it more

I’ve benefited greatly from these notes, thank you.

This is very helpful

well articulated ideas are presented here, thank you for being reliable sources of information

Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)

I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?

Angelo Loye Very fantastic information. From here I am going straightaway to present the research hypothesis One question, do we apply hypothesis in qualitative research? What nul hypothesi Otherwise I appreciate your research methodo

this is very important note help me much more

Hi” best wishes to you and your very nice blog” 

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Definition of a Hypothesis

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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.

Within social science, a hypothesis can take two forms. It can predict that there is no relationship between two variables, in which case it is a null hypothesis . Or, it can predict the existence of a relationship between variables, which is known as an alternative hypothesis.

In either case, the variable that is thought to either affect or not affect the outcome is known as the independent variable, and the variable that is thought to either be affected or not is the dependent variable.

Researchers seek to determine whether or not their hypothesis, or hypotheses if they have more than one, will prove true. Sometimes they do, and sometimes they do not. Either way, the research is considered successful if one can conclude whether or not a hypothesis is true. 

Null Hypothesis

A researcher has a null hypothesis when she or he believes, based on theory and existing scientific evidence, that there will not be a relationship between two variables. For example, when examining what factors influence a person's highest level of education within the U.S., a researcher might expect that place of birth, number of siblings, and religion would not have an impact on the level of education. This would mean the researcher has stated three null hypotheses.

Alternative Hypothesis

Taking the same example, a researcher might expect that the economic class and educational attainment of one's parents, and the race of the person in question are likely to have an effect on one's educational attainment. Existing evidence and social theories that recognize the connections between wealth and cultural resources , and how race affects access to rights and resources in the U.S. , would suggest that both economic class and educational attainment of the one's parents would have a positive effect on educational attainment. In this case, economic class and educational attainment of one's parents are independent variables, and one's educational attainment is the dependent variable—it is hypothesized to be dependent on the other two.

Conversely, an informed researcher would expect that being a race other than white in the U.S. is likely to have a negative impact on a person's educational attainment. This would be characterized as a negative relationship, wherein being a person of color has a negative effect on one's educational attainment. In reality, this hypothesis proves true, with the exception of Asian Americans , who go to college at a higher rate than whites do. However, Blacks and Hispanics and Latinos are far less likely than whites and Asian Americans to go to college.

Formulating a Hypothesis

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.

Updated by Nicki Lisa Cole, Ph.D

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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

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• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when  conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a  correlational study  can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Research Hypothesis In Psychology: Types, & Examples

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .

Hypotheses connect theory to data and guide the research process towards expanding scientific understanding

Some key points about hypotheses:

• A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
• It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
• A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
• Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
• For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
• Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.

Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.

Types of Research Hypotheses

Alternative hypothesis.

The research hypothesis is often called the alternative or experimental hypothesis in experimental research.

It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.

The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).

A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:

• Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.

In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.

An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.

It states that the results are not due to chance and are significant in supporting the theory being investigated.

The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.

Null Hypothesis

The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.

It states results are due to chance and are not significant in supporting the idea being investigated.

The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.

Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.

This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.

Nondirectional Hypothesis

A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.

It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.

For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.

Directional Hypothesis

A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)

It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.

For example, “Exercise increases weight loss” is a directional hypothesis.

Falsifiability

The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.

Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.

It means that there should exist some potential evidence or experiment that could prove the proposition false.

However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.

For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.

Can a Hypothesis be Proven?

Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.

All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.

In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.

• Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
• However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.

We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.

If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.

Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.

How to Write a Hypothesis

• Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
• Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
• Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
• Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
• Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.

Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).

Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:

• The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
• The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.

More Examples

• Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
• Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
• Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
• Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
• Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
• Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
• Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
• Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.

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Hypotheses: meaning, types and sources | social research.

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After reading this article you will learn about:- 1. Meaning of Hypotheses 2. Types of Hypotheses 3. Sources.

Meaning of Hypotheses:

Once the problem to be answered in the course of research is finally instituted, the researcher may, if feasible proceed to formulate tentative solutions or answers to it. These proposed solutions or explanations are called hypotheses which the researcher is obliged to test on the basis of fact already known or which can be made known.

If such answers are not formulated, even implicitly, the researcher cannot effectively go ahead with the investigation of his problem because, in the absence of direction which hypotheses typically provide, the researcher would not know what facts to look for and what relation or order to search for amongst them.

The hypotheses guide the researcher through a bewildering Jungle of facts to see and select only those that are relevant to the problem or difficulty he proposes to solve. Collection of facts merely for the sake of collecting them will yield no fruits.

To be fruitful, one should collect such facts as are for or against some point of view or proposition. Such a point of view or proposition is the hypothesis. The task of the inquiry or research is to test its accord with facts.

Lundberg aptly observes, “The only difference between gathering data without a hypothesis and gathering them with one, is that in the latter case, we deliberately recognize the limitations of our senses and attempt to reduce their fallibility by limiting our field of investigation so as to prevent greater concentration for attention on particular aspects which past experience leads us to believe are irrelevant as insignificant for our purpose.”

Simply stated, an hypothesis helps us see and appreciate:

(1) The kind of data that need be collected in order to answer the research question and

(2) The way in which they should be organized most efficiently and meaningfully.

Webster’s New International Dictionary of English Language, 1956, defines the term “hypothesis” as “proposition, condition or principle which is assumed, perhaps without belief, in order to draw out its logical consequences and by this method to test its accord with facts which are known or may be determined.”

Cohen and Nagel bring out the value of hypothesis thus:

“We cannot take a single step forward in any inquiry unless we begin with a suggested explanation or solution of the difficulty which originated it. Such tentative explanations are suggested to us by something in the subject-matter and by our previous knowledge. When they are formulated as propositions, they are called hypotheses.”

Once the scientist knows what his question (problem) is, he can make a guess, or a number of guesses as to its possible answers. According to Werkmeister, “The guesses he makes are the hypotheses which either solve the problems or guide him in further investigation.”

It is clear now that a hypothesis is a provisional formulation; a tentative solution of the problem posed by the scientist. ‘The scientist starts by assuming that the solution is true without, of course, personally believing in its truthfulness.

Based on this assumption, the scientist anticipates that certain logical consequences will be observed on the plane of observable events or objects. Whether these anticipations or expectations really materialize is the test of the hypothesis, its proof or disproof.

If the hypothesis is proved, the problem of which it was a tentative solution is answered. If it is not proved, i.e., falsified owing to non-support of proof, alternative hypotheses may be formulated by the researcher. An hypothesis thus stands somewhere at the midpoint of research; from here, one can look back to the problem as also look forward to data.

The hypothesis may be stated in the form of a principle, that is, the tentative explanation or solution to the questions how? Or why? May be presented in the form of a principle that X varies with Y. The inquiry established that an empirical referent of X varies with the empirical referent of Y in a concrete observable situation (i.e., the hypothesis is proved) then the question is answered.

Hypotheses, however, may take other forms, such as intelligent guesses, conditions, propositions deduced from theories, observations and findings of other scholars etc.

Proceeding on the basis of hypotheses has been the slow and hard way of science. While some scientific conclusions and premises seem to have arisen in the mind of the investigator as if by flashes of insight, in a majority of cases the process of discovery has been a slower one.

“The scientific imagination devises a possible solution, a hypothesis and the investigator proceeds to test it. He makes intellectual keys and then tries to see whether they fit the lock. If the hypothesis does not fit, it is rejected and another is made. The scientific workshop is full of discarded keys.”

Cohen and Nagel’s statement that one cannot take a single step forward in any inquiry without a hypothesis may well be a correct statement of the value of hypothesis in scientific investigation generally, but it hardly does justice to an important function of scientific research, i.e., the “formulation hypotheses.”

Hypotheses are not given to us readymade. Of course in fields with a highly developed theoretic structure it is reasonable to expect that most empirical studies will have at least some sharp hypotheses to be tested.

This is so especially in social sciences where there has not yet evolved a highly developed theoretic system in many areas of its subject-matter which can afford fruitful bases for hypothesis-formulation.

As such, attempts to force research into this mould are either deceitful or stultifying and hypotheses are likely to be no more than hunches as to where to look for sharper hypotheses in which case the study may be described as an intelligent fishing trip.

As a result, in the social sciences at least, a considerable quantum of research endeavour is directed understandably toward ‘making’ hypotheses rather than at testing them.

A very important type of research has as its goal, the formulation of significant hypotheses relating to a particular problem. Hence, we will do well to bear in mind that research can begin with well formulated hypotheses or it may come out with hypotheses as its end product.

Let us recapitulate the role of hypotheses for research in the words of Chaddock who summarizes it thus:

“(A hypothesis) in the scientific sense is … an explanation held after careful canvass of known facts, in full knowledge of other explanations that have been offered and with a mind open to change of view, if the facts disclosed by the inquiry warrant a different explanation. Another hypothesis as an explanation is proposed including investigation all available and pertinent data either to prove or disprove the hypothesis…. (A hypothesis) gives point to the inquiry and if founded on sufficient previous knowledge, guides the line of investigation. Without it much useless data maybe collected in the hope that nothing essential will be omitted or important data may be omitted which could have been easily included if the purpose of inquiry had been more clearly defined” and thus hypotheses are likely to be no more than hunches as to where to look for pertinent data.

An hypothesis is therefore held with the definite purpose of including in the investigating all available and pertinent data either to prove or disprove the hypothesis.

Types of Hypotheses :

There are many kinds of hypotheses the social researcher has to be working with. One type of hypotheses asserts that something is the case in a given instance; that a particular object, person or situation has a particular characteristic.

Another type of hypotheses deals with the frequency of occurrences or of association among variables; this type of hypotheses may state that X is associated with y a certain (Y) proportion of times, e.g., that urbanism tends to be accompanied by mental disease or that something is greater or lesser than some thing else in a specific setting.

Yet another type of hypotheses assert that a particular characteristic is one of the factors which determine another characteristic, i.e., S is the producer of Y (product). Hypotheses of this type are known as causal hypotheses.

Hypotheses can be classified in a variety of ways. But classification of hypotheses on the basis of their levels of abstraction is regarded as especially fruitful. Goode arid Hatt have identified three differential levels of abstraction reached by hypotheses. We shall here be starting from the lowest level of abstraction and go over to the higher ones.

(a) At the lowest level of abstraction are the hypotheses which state existence of certain empirical uniformities. Many types of such empirical uniformities are common in social research, for instance, it may be hypothesized with reference to India that in the cities men will get married between the age of 22 and 24 years.

Or, the hypotheses of this type may state that certain behaviour pattern may be expected in a specified community. Thus, hypotheses of this type frequently seem to invite scientific verification of what are called “common sense propositions,” indeed without much justification.

It has often been said by way of a criticism of such hypotheses that these are not useful in as much as they merely state what everyone seems to know already. Such an objection may however be overruled by pointing out that what everyone knows is not often put in precise terms nor is it adequately integrated into the framework of science.

Secondly, what everyone knows may well be mistaken. To put common sense ideas into precisely defined concepts and subject the proposition to test is an important task of science.

This is particularly applicable to social sciences which are at present in their earlier stage of development. Not only social science but all sciences have found such commonsense knowledge a fruitful item of study. It was commonsense knowledge in the olden days that sun revolved round the earth. But this and many other beliefs based on commonsense have been exploded by patient, plodding, empirical checking of facts.

The monumental work, The American Soldier by Stouffer and associates was criticized in certain quarters, for it was according to them mere elaboration of the obvious. But to this study goes the credit of exploding some of the commonsense propositions and shocking many people who had never thought that what was so obvious a commonsense could be totally wrong or unfounded in fact.

(b) At a relatively higher level of abstraction are hypotheses concerned with complex ‘ideal types.’ These hypotheses aim at testing whether logically derived relationship between empirical uniformities obtain. This level of hypothesizing moves beyond the level of anticipating a simple empirical uniformity by visualizing a complex referent in society.

Such hypotheses are indeed purposeful distortions of empirical exactness and owing to their remoteness from empirical reality, these constructs are termed ‘ideal types.’ The function of such hypotheses is to create tools and formulate problems for further research in complex areas of investigation.

An example of one such hypothesis may be cited. Analyses of minority groups brought to light empirical uniformities in the behaviour of members of a wide variety of minorities. It was subsequently hypothesized that these uniformities pointed to an ‘ideal type’.

First called by H. A. Miller the ‘oppression psychosis,’ this ideal-typical construction was subsequently modified as the ‘Marginal man’ by E. Stone Quist and associates. Empirical evidence marshaled later substantiated the hypothesis, and so the concept of marginality (marginal man) has very much come to stay as a theoretic construct in social sciences, and as part of sociological theory.

(c) We now come to the class of hypotheses at the highest level of abstraction. This category of hypotheses is concerned with the relation obtaining amongst analytic variables. Such hypotheses are statements about, how one property affects other, e.g., a statement of relationship between education and social mobility or between wealth and fertility.

It is easy to see that this level of hypothesizing is not only more abstract compared to others; it is also the most sophisticated and vastly flexible mode of formulation.

This does not mean, however, that this type of hypotheses is ‘superior’ or ‘better’ than the other types. Each type of hypotheses has its own importance depending in turn upon the nature of investigation and the level of development the subject has achieved.

The sophisticated hypotheses of analytical variables owe much of their existence to the building-blocks contributed by the hypotheses existed at the lower orders of abstraction.

Sources of Hypotheses :

Hypotheses may be developed from a variety of sources. We examine here, some of the major ones.

(1) The history of sciences provides an eloquent testimony to the fact that personal and idiosyncratic experiences of the scientist contribute a great deal to type and form of questions he may ask, as also to the kinds of tentative answers to these questions (hypotheses) that he might provide. Some scientists may perceive an interesting pattern in what may merely, seem a jumble of facts to the common man.

The history of science is full of instances of discoveries made just because the ‘right’ person happened to make the ‘right’ observation owing to his characteristic life-history and exposure to a unique mosaic of events. Personal life-histories are a factor in determining the kinds of a person’s perception and conception and this factor may in turn direct him to certain hypotheses quite readily.

An illustration of such individual perspectives in social sciences may be seen in the work of Thorstein Veblen whom Merton describes as a sociologist with a keen eye for the unusual and paradoxical.

A product of an isolated Norwegian community, Veblen lived at a time when the capitalistic system was barely subjected to any criticism. His own community background was replete with derivational experiences attributable to the capitalist system.

Veblen being an outsider, was able to look at the capitalist economic system more objectively and with dispassionate detachment. Veblen was thus strategically positioned to attack the fundamental concepts and postulates of classical economics.

He was an alien who could bring a different experience to bear upon the economic world. Consequently, he made penetrating analyses of society and economy which have ever since profoundly influenced social science.

(2) Analogies are often a fountainhead of valuable hypotheses. Students of sociology and political science in the course of their studies would have come across analogies wherein society and state are compared to a biological organism, the natural law to the social law, thermodynamics to social dynamics, etc. such analogies, notwithstanding the fact that analogies as a class suffer from serious limitations, do provide certain fruitful insight which formulated as hypotheses stimulate and guide inquiries.

One of the recent orientations to hypotheses formulation is provided by cybernetics, the communication models now so well entrenched in the social science testify to the importance of analogies as a source of fruitful hypotheses. The hypothesis that similar human types or activities may be found occupying the same territory was derived from plant ecology.

When the hypothesis was borne out by observations in society, the concept of segregation as it is called in plant ecology was admitted into sociology. It has now become an important idea in sociological theory. Such examples may be multiplied.

In sum, analogy may be very suggestive but care needs to be taken not to accept models from other disciplines without a careful scrutiny of the concepts in terms of their applicability to the new frame of reference in which they are proposed to be deployed.

(3) Hypotheses may rest also on the findings of other studies. The researcher on the basis of the findings of other studies may hypothesize that similar relationship between specified variables will hold good in the present study too. This is a common way of researchers who design their study with a view of replicating another study conducted in a different concrete context or setting.

It was said that many a study in social science is exploratory in character, i.e., they start without explicit hypotheses, the findings of such studies may be formulated as hypotheses for more structured investigations directed at testing certain hypotheses.

(4) An hypothesis may stem from a body of theory which may afford by way of logical deduction, the prediction that if certain conditions are present, certain results will follow. Theory represents what is known; logical deductions from this constitute the hypotheses which must be true if the theory was true.

Dubin aptly remarks, “Hypothesis is the feature of the theoretical model closest to the ‘things observable’ that the theory is trying to model.” Merton illustrates this function of theory with his customary felicity. Basing his deductions on Durham’s theoretic orientation, Merton shows how hypotheses may be derived as deductions from theoretic system.

(1) Social cohesion provides psychic support to group members subjected to acute stresses and anxieties.

(2) Suicide rates are functions of unrelieved anxieties to which persons are subjected.

(3) Catholics have greater social cohesion than protestants.

(4) Therefore, lower suicide rates should be expected among Catholics than among protestants.

If theories purport to model the empirical world, then there must be a linkage between the two. This linkage is to be found in the hypotheses that mirror the propositions of the theoretical model.

It may thus appear that the points of departure vis-a-vis hypotheses-construction are in two opposite directions:

(a) Conclusions based on concrete or empirical observations lead through the process of induction to more abstract hypotheses and

(b) The theoretical model through the process of logical deduction affords more concrete hypotheses.

It may be well to bear in mind, however, that although these two approaches to hypotheses formulation seem diametrically opposed to each other, the two points of departure, i.e., empirical, observations and the theoretical structure, represent the poles of a continuum and hypotheses lie somewhere in the middle of this continuum.

Both these approaches to hypotheses-construction have proved their worth. The Chicago School in American sociology represents a strong empirical orientation whereas the Mertonian and Parsonian approach is typified by a stress on theoretic models as initial bases for hypotheses-construction. Hence hypotheses can be deductively derived from theoretic models.

(5) It is worthy of note that value-orientation of the culture in which a science develops may furnish many of its basic hypotheses.

That certain hypotheses and not others capture the attention of scientists or occur to them in particular societies or culture may well be attributed to the cultural emphases. Goode and Hatt contend that the American emphasis upon personal happiness had had considerable effect upon social science in that country.

The phenomenon of personal happiness has been studied in great detail. In every branch of social science, the problem of personal happiness came to occupy a position meriting central focus. Happiness has been correlated with income, education, occupation, social class, and so on. It is evident that the culture emphasis on happiness has been productive of a very wide range of hypotheses for the American social science.

Folk-wisdom prevalent in a culture may also serve as source of hypotheses. The sum and substance of the discussion is aptly reflected in Larrabee’s remark that the ideal source of fruitful and relevant hypotheses is a fusion of two elements: past experience and imagination in the disciplined mind of the scientist.

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• Role of Hypothesis in Social Research
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Research , Social Research , Hypotheses

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Table of Contents

What is Hypothesis?

• Hypothesis is a logical prediction of certain occurrences without the support of empirical confirmation or evidence.
• In scientific terms, it is a tentative theory or testable statement about the relationship between two or more variables i.e. independent and dependent variable.

Different Types of Hypothesis:

1. Simple Hypothesis:

• A Simple hypothesis is also known as composite hypothesis.
• In simple hypothesis all parameters of the distribution are specified.
• It predicts relationship between two variables i.e. the dependent and the independent variable

2. Complex Hypothesis:

• A Complex hypothesis examines relationship between two or more independent variables and two or more dependent variables.

3. Working or Research Hypothesis:

• A research hypothesis is a specific, clear prediction about the possible outcome of a scientific research study based on specific factors of the population.

4. Null Hypothesis:

• A null hypothesis is a general statement which states no relationship between two variables or two phenomena. It is usually denoted by H 0 .

5. Alternative Hypothesis:

• An alternative hypothesis is a statement which states some statistical significance between two phenomena. It is usually denoted by H 1 or H A .

6. Logical Hypothesis:

• A logical hypothesis is a planned explanation holding limited evidence.

7. Statistical Hypothesis:

• A statistical hypothesis, sometimes called confirmatory data analysis, is an assumption about a population parameter.

Although there are different types of hypothesis, the most commonly and used hypothesis are Null hypothesis and alternate hypothesis . So, what is the difference between null hypothesis and alternate hypothesis? Let’s have a look:

Major Differences Between Null Hypothesis and Alternative Hypothesis:

Importance of hypothesis:.

• It ensures the entire research methodologies are scientific and valid.
• It helps to assume the probability of research failure and progress.
• It helps to provide link to the underlying theory and specific research question.
• It helps in data analysis and measure the validity and reliability of the research.
• It provides a basis or evidence to prove the validity of the research.
• It helps to describe research study in concrete terms rather than theoretical terms.

Characteristics of Good Hypothesis:

• Should be simple.
• Should be specific.
• Should be stated in advance.

References and For More Information:

https://ocw.jhsph.edu/courses/StatisticalReasoning1/PDFs/2009/BiostatisticsLecture4.pdf

https://keydifferences.com/difference-between-type-i-and-type-ii-errors.html

https://www.khanacademy.org/math/ap-statistics/tests-significance-ap/error-probabilities-power/a/consequences-errors-significance

https://stattrek.com/hypothesis-test/hypothesis-testing.aspx

http://davidmlane.com/hyperstat/A2917.html

https://study.com/academy/lesson/what-is-a-hypothesis-definition-lesson-quiz.html

https://keydifferences.com/difference-between-null-and-alternative-hypothesis.html

https://blog.minitab.com/blog/adventures-in-statistics-2/understanding-hypothesis-tests-why-we-need-to-use-hypothesis-tests-in-statistics

• Characteristics of Good Hypothesis
• complex hypothesis
• example of alternative hypothesis
• example of null hypothesis
• how is null hypothesis different to alternative hypothesis
• Importance of Hypothesis
• null hypothesis vs alternate hypothesis
• simple hypothesis
• Types of Hypotheses
• what is alternate hypothesis
• what is alternative hypothesis
• what is hypothesis?
• what is logical hypothesis
• what is null hypothesis
• what is research hypothesis
• what is statistical hypothesis
• why is hypothesis necessary

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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

Hypotheses are crucial in social research, guiding the research process and providing a framework for testing theories and drawing conclusions. This essay discusses the importance and sources of hypotheses in social research.

Importance of Hypotheses:

1. Guiding the research process: Hypotheses provide direction and focus, helping researchers design studies, select methods, and collect data. For example, a researcher studying education and income might hypothesize that higher education leads to higher income, guiding variable selection and data collection.

2. Facilitating theory testing: Hypotheses allow researchers to test theories by making predictions about variable relationships. Robert Merton’s theory of anomie suggests deviant behavior occurs when there is a discrepancy between goals and means, which can be tested through hypotheses.

3. Enabling empirical verification: Hypotheses are testable statements verified through observation and data collection, establishing validity and reliability. For example, a researcher can test the hypothesis that social media use decreases face-to-face interactions.

4. Promoting scientific inquiry: Hypotheses encourage critical thinking about social phenomena, generating new ideas. Émile Durkheim’s hypothesis about social integration and suicide rates led to insights into social factors influencing suicidal behavior.

Sources of Hypotheses:

1. Theories and literature: Existing theories and research serve as sources of hypotheses. Pierre Bourdieu’s theory of cultural capital might inspire a hypothesis about socioeconomic background and academic success.

2. Observations and experiences: Researchers’ observations can inspire hypotheses. Observing gender differences in classroom participation might lead to hypotheses about gender stereotypes and engagement.

3. Analogies and comparisons: Comparing social phenomena can generate hypotheses about underlying mechanisms. Comparing parenting styles and child development might yield hypotheses about parental control and warmth.

4. Collaborative discussions: Discussions with colleagues or stakeholders can stimulate hypothesis generation. Discussing immigrant challenges might lead to hypotheses about social support and integration.

5. Logical reasoning: Hypotheses can be derived through logical reasoning. Analyzing poverty and crime might lead to hypotheses about limited opportunities and social strain.

Conclusion: Hypotheses guide research, facilitate theory testing, enable verification, and promote inquiry. Researchers can generate hypotheses from theories, observations, analogies, discussions, and reasoning, contributing to the advancement of sociological knowledge.

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