difficulties in formulation of hypothesis

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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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

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

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

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

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

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

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

Variables in hypotheses

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

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

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

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

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Step 1. Ask a question

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

Step 2. Do some preliminary research

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

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

Step 3. Formulate your hypothesis

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

4. Refine your hypothesis

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

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

5. Phrase your hypothesis in three ways

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

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

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

6. Write a null hypothesis

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

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

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

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

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

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

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Formulating Hypotheses for Different Study Designs

Durga prasanna misra.

1 Department of Clinical Immunology and Rheumatology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.

Armen Yuri Gasparyan

2 Departments of Rheumatology and Research and Development, Dudley Group NHS Foundation Trust (Teaching Trust of the University of Birmingham, UK), Russells Hall Hospital, Dudley, UK.

Olena Zimba

3 Department of Internal Medicine #2, Danylo Halytsky Lviv National Medical University, Lviv, Ukraine.

Marlen Yessirkepov

4 Department of Biology and Biochemistry, South Kazakhstan Medical Academy, Shymkent, Kazakhstan.

Vikas Agarwal

George d. kitas.

5 Centre for Epidemiology versus Arthritis, University of Manchester, Manchester, UK.

Generating a testable working hypothesis is the first step towards conducting original research. Such research may prove or disprove the proposed hypothesis. Case reports, case series, online surveys and other observational studies, clinical trials, and narrative reviews help to generate hypotheses. Observational and interventional studies help to test hypotheses. A good hypothesis is usually based on previous evidence-based reports. Hypotheses without evidence-based justification and a priori ideas are not received favourably by the scientific community. Original research to test a hypothesis should be carefully planned to ensure appropriate methodology and adequate statistical power. While hypotheses can challenge conventional thinking and may be controversial, they should not be destructive. A hypothesis should be tested by ethically sound experiments with meaningful ethical and clinical implications. The coronavirus disease 2019 pandemic has brought into sharp focus numerous hypotheses, some of which were proven (e.g. effectiveness of corticosteroids in those with hypoxia) while others were disproven (e.g. ineffectiveness of hydroxychloroquine and ivermectin).

Graphical Abstract

DEFINING WORKING AND STANDALONE SCIENTIFIC HYPOTHESES

Science is the systematized description of natural truths and facts. Routine observations of existing life phenomena lead to the creative thinking and generation of ideas about mechanisms of such phenomena and related human interventions. Such ideas presented in a structured format can be viewed as hypotheses. After generating a hypothesis, it is necessary to test it to prove its validity. Thus, hypothesis can be defined as a proposed mechanism of a naturally occurring event or a proposed outcome of an intervention. 1 , 2

Hypothesis testing requires choosing the most appropriate methodology and adequately powering statistically the study to be able to “prove” or “disprove” it within predetermined and widely accepted levels of certainty. This entails sample size calculation that often takes into account previously published observations and pilot studies. 2 , 3 In the era of digitization, hypothesis generation and testing may benefit from the availability of numerous platforms for data dissemination, social networking, and expert validation. Related expert evaluations may reveal strengths and limitations of proposed ideas at early stages of post-publication promotion, preventing the implementation of unsupported controversial points. 4

Thus, hypothesis generation is an important initial step in the research workflow, reflecting accumulating evidence and experts' stance. In this article, we overview the genesis and importance of scientific hypotheses and their relevance in the era of the coronavirus disease 2019 (COVID-19) pandemic.

DO WE NEED HYPOTHESES FOR ALL STUDY DESIGNS?

Broadly, research can be categorized as primary or secondary. In the context of medicine, primary research may include real-life observations of disease presentations and outcomes. Single case descriptions, which often lead to new ideas and hypotheses, serve as important starting points or justifications for case series and cohort studies. The importance of case descriptions is particularly evident in the context of the COVID-19 pandemic when unique, educational case reports have heralded a new era in clinical medicine. 5

Case series serve similar purpose to single case reports, but are based on a slightly larger quantum of information. Observational studies, including online surveys, describe the existing phenomena at a larger scale, often involving various control groups. Observational studies include variable-scale epidemiological investigations at different time points. Interventional studies detail the results of therapeutic interventions.

Secondary research is based on already published literature and does not directly involve human or animal subjects. Review articles are generated by secondary research. These could be systematic reviews which follow methods akin to primary research but with the unit of study being published papers rather than humans or animals. Systematic reviews have a rigid structure with a mandatory search strategy encompassing multiple databases, systematic screening of search results against pre-defined inclusion and exclusion criteria, critical appraisal of study quality and an optional component of collating results across studies quantitatively to derive summary estimates (meta-analysis). 6 Narrative reviews, on the other hand, have a more flexible structure. Systematic literature searches to minimise bias in selection of articles are highly recommended but not mandatory. 7 Narrative reviews are influenced by the authors' viewpoint who may preferentially analyse selected sets of articles. 8

In relation to primary research, case studies and case series are generally not driven by a working hypothesis. Rather, they serve as a basis to generate a hypothesis. Observational or interventional studies should have a hypothesis for choosing research design and sample size. The results of observational and interventional studies further lead to the generation of new hypotheses, testing of which forms the basis of future studies. Review articles, on the other hand, may not be hypothesis-driven, but form fertile ground to generate future hypotheses for evaluation. Fig. 1 summarizes which type of studies are hypothesis-driven and which lead on to hypothesis generation.

STANDARDS OF WORKING AND SCIENTIFIC HYPOTHESES

A review of the published literature did not enable the identification of clearly defined standards for working and scientific hypotheses. It is essential to distinguish influential versus not influential hypotheses, evidence-based hypotheses versus a priori statements and ideas, ethical versus unethical, or potentially harmful ideas. The following points are proposed for consideration while generating working and scientific hypotheses. 1 , 2 Table 1 summarizes these points.

Evidence-based data

A scientific hypothesis should have a sound basis on previously published literature as well as the scientist's observations. Randomly generated (a priori) hypotheses are unlikely to be proven. A thorough literature search should form the basis of a hypothesis based on published evidence. 7

Unless a scientific hypothesis can be tested, it can neither be proven nor be disproven. Therefore, a scientific hypothesis should be amenable to testing with the available technologies and the present understanding of science.

Supported by pilot studies

If a hypothesis is based purely on a novel observation by the scientist in question, it should be grounded on some preliminary studies to support it. For example, if a drug that targets a specific cell population is hypothesized to be useful in a particular disease setting, then there must be some preliminary evidence that the specific cell population plays a role in driving that disease process.

Testable by ethical studies

The hypothesis should be testable by experiments that are ethically acceptable. 9 For example, a hypothesis that parachutes reduce mortality from falls from an airplane cannot be tested using a randomized controlled trial. 10 This is because it is obvious that all those jumping from a flying plane without a parachute would likely die. Similarly, the hypothesis that smoking tobacco causes lung cancer cannot be tested by a clinical trial that makes people take up smoking (since there is considerable evidence for the health hazards associated with smoking). Instead, long-term observational studies comparing outcomes in those who smoke and those who do not, as was performed in the landmark epidemiological case control study by Doll and Hill, 11 are more ethical and practical.

Balance between scientific temper and controversy

Novel findings, including novel hypotheses, particularly those that challenge established norms, are bound to face resistance for their wider acceptance. Such resistance is inevitable until the time such findings are proven with appropriate scientific rigor. However, hypotheses that generate controversy are generally unwelcome. For example, at the time the pandemic of human immunodeficiency virus (HIV) and AIDS was taking foot, there were numerous deniers that refused to believe that HIV caused AIDS. 12 , 13 Similarly, at a time when climate change is causing catastrophic changes to weather patterns worldwide, denial that climate change is occurring and consequent attempts to block climate change are certainly unwelcome. 14 The denialism and misinformation during the COVID-19 pandemic, including unfortunate examples of vaccine hesitancy, are more recent examples of controversial hypotheses not backed by science. 15 , 16 An example of a controversial hypothesis that was a revolutionary scientific breakthrough was the hypothesis put forth by Warren and Marshall that Helicobacter pylori causes peptic ulcers. Initially, the hypothesis that a microorganism could cause gastritis and gastric ulcers faced immense resistance. When the scientists that proposed the hypothesis themselves ingested H. pylori to induce gastritis in themselves, only then could they convince the wider world about their hypothesis. Such was the impact of the hypothesis was that Barry Marshall and Robin Warren were awarded the Nobel Prize in Physiology or Medicine in 2005 for this discovery. 17 , 18

DISTINGUISHING THE MOST INFLUENTIAL HYPOTHESES

Influential hypotheses are those that have stood the test of time. An archetype of an influential hypothesis is that proposed by Edward Jenner in the eighteenth century that cowpox infection protects against smallpox. While this observation had been reported for nearly a century before this time, it had not been suitably tested and publicised until Jenner conducted his experiments on a young boy by demonstrating protection against smallpox after inoculation with cowpox. 19 These experiments were the basis for widespread smallpox immunization strategies worldwide in the 20th century which resulted in the elimination of smallpox as a human disease today. 20

Other influential hypotheses are those which have been read and cited widely. An example of this is the hygiene hypothesis proposing an inverse relationship between infections in early life and allergies or autoimmunity in adulthood. An analysis reported that this hypothesis had been cited more than 3,000 times on Scopus. 1

LESSONS LEARNED FROM HYPOTHESES AMIDST THE COVID-19 PANDEMIC

The COVID-19 pandemic devastated the world like no other in recent memory. During this period, various hypotheses emerged, understandably so considering the public health emergency situation with innumerable deaths and suffering for humanity. Within weeks of the first reports of COVID-19, aberrant immune system activation was identified as a key driver of organ dysfunction and mortality in this disease. 21 Consequently, numerous drugs that suppress the immune system or abrogate the activation of the immune system were hypothesized to have a role in COVID-19. 22 One of the earliest drugs hypothesized to have a benefit was hydroxychloroquine. Hydroxychloroquine was proposed to interfere with Toll-like receptor activation and consequently ameliorate the aberrant immune system activation leading to pathology in COVID-19. 22 The drug was also hypothesized to have a prophylactic role in preventing infection or disease severity in COVID-19. It was also touted as a wonder drug for the disease by many prominent international figures. However, later studies which were well-designed randomized controlled trials failed to demonstrate any benefit of hydroxychloroquine in COVID-19. 23 , 24 , 25 , 26 Subsequently, azithromycin 27 , 28 and ivermectin 29 were hypothesized as potential therapies for COVID-19, but were not supported by evidence from randomized controlled trials. The role of vitamin D in preventing disease severity was also proposed, but has not been proven definitively until now. 30 , 31 On the other hand, randomized controlled trials identified the evidence supporting dexamethasone 32 and interleukin-6 pathway blockade with tocilizumab as effective therapies for COVID-19 in specific situations such as at the onset of hypoxia. 33 , 34 Clues towards the apparent effectiveness of various drugs against severe acute respiratory syndrome coronavirus 2 in vitro but their ineffectiveness in vivo have recently been identified. Many of these drugs are weak, lipophilic bases and some others induce phospholipidosis which results in apparent in vitro effectiveness due to non-specific off-target effects that are not replicated inside living systems. 35 , 36

Another hypothesis proposed was the association of the routine policy of vaccination with Bacillus Calmette-Guerin (BCG) with lower deaths due to COVID-19. This hypothesis emerged in the middle of 2020 when COVID-19 was still taking foot in many parts of the world. 37 , 38 Subsequently, many countries which had lower deaths at that time point went on to have higher numbers of mortality, comparable to other areas of the world. Furthermore, the hypothesis that BCG vaccination reduced COVID-19 mortality was a classic example of ecological fallacy. Associations between population level events (ecological studies; in this case, BCG vaccination and COVID-19 mortality) cannot be directly extrapolated to the individual level. Furthermore, such associations cannot per se be attributed as causal in nature, and can only serve to generate hypotheses that need to be tested at the individual level. 39

IS TRADITIONAL PEER REVIEW EFFICIENT FOR EVALUATION OF WORKING AND SCIENTIFIC HYPOTHESES?

Traditionally, publication after peer review has been considered the gold standard before any new idea finds acceptability amongst the scientific community. Getting a work (including a working or scientific hypothesis) reviewed by experts in the field before experiments are conducted to prove or disprove it helps to refine the idea further as well as improve the experiments planned to test the hypothesis. 40 A route towards this has been the emergence of journals dedicated to publishing hypotheses such as the Central Asian Journal of Medical Hypotheses and Ethics. 41 Another means of publishing hypotheses is through registered research protocols detailing the background, hypothesis, and methodology of a particular study. If such protocols are published after peer review, then the journal commits to publishing the completed study irrespective of whether the study hypothesis is proven or disproven. 42 In the post-pandemic world, online research methods such as online surveys powered via social media channels such as Twitter and Instagram might serve as critical tools to generate as well as to preliminarily test the appropriateness of hypotheses for further evaluation. 43 , 44

Some radical hypotheses might be difficult to publish after traditional peer review. These hypotheses might only be acceptable by the scientific community after they are tested in research studies. Preprints might be a way to disseminate such controversial and ground-breaking hypotheses. 45 However, scientists might prefer to keep their hypotheses confidential for the fear of plagiarism of ideas, avoiding online posting and publishing until they have tested the hypotheses.

SUGGESTIONS ON GENERATING AND PUBLISHING HYPOTHESES

Publication of hypotheses is important, however, a balance is required between scientific temper and controversy. Journal editors and reviewers might keep in mind these specific points, summarized in Table 2 and detailed hereafter, while judging the merit of hypotheses for publication. Keeping in mind the ethical principle of primum non nocere, a hypothesis should be published only if it is testable in a manner that is ethically appropriate. 46 Such hypotheses should be grounded in reality and lend themselves to further testing to either prove or disprove them. It must be considered that subsequent experiments to prove or disprove a hypothesis have an equal chance of failing or succeeding, akin to tossing a coin. A pre-conceived belief that a hypothesis is unlikely to be proven correct should not form the basis of rejection of such a hypothesis for publication. In this context, hypotheses generated after a thorough literature search to identify knowledge gaps or based on concrete clinical observations on a considerable number of patients (as opposed to random observations on a few patients) are more likely to be acceptable for publication by peer-reviewed journals. Also, hypotheses should be considered for publication or rejection based on their implications for science at large rather than whether the subsequent experiments to test them end up with results in favour of or against the original hypothesis.

Hypotheses form an important part of the scientific literature. The COVID-19 pandemic has reiterated the importance and relevance of hypotheses for dealing with public health emergencies and highlighted the need for evidence-based and ethical hypotheses. A good hypothesis is testable in a relevant study design, backed by preliminary evidence, and has positive ethical and clinical implications. General medical journals might consider publishing hypotheses as a specific article type to enable more rapid advancement of science.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Data curation: Gasparyan AY, Misra DP, Zimba O, Yessirkepov M, Agarwal V, Kitas GD.

Investigation and Management of Disease in Wild Animals pp 73–86 Cite as

Formulating and Testing Hypotheses

• Gary A. Wobeser 2  

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The term hypothesis has been mentioned several times in the preceding chapters. The definition that will be used here is that a hypothesis is a proposition set forth as explanation for the occurrence of a specified phenomenon. The basis of scientific investigation is the collection of information that is used either to formulate or to test hypotheses. One assesses the important variables and tries to build a model or hypothesis that explains the observed phenomenon. In general, a hypothesis is formulated by rephrasing the objective of a study as a statement, e.g., if the objective of an investigation is to determine if a pesticide is safe, the resulting hypothesis might be “ the pesticide is not safe ”, or alternatively that “ the pesticide is safe ”. A hypothesis is a statistical hypothesis only if it is stated in terms related to the distribution of populations. The general hypothesis above might be refined to: “ this pesticide, when used as directed, has no effect on the average number of robins in an area ”, which is a testable hypothesis. The hypothesis to be tested is called the null hypothesis (H 0 ). The alternative hypothesis (H 1 ) for the above example would be “ this pesticide, when used as directed, has an effect on the average number of robins in an area”. In testing a hypothesis, H 0 is considered to be true, unless the sample data indicate otherwise, (i.e., that the pesticide is innocent, unless proven guilty). Testing cannot prove H 0 to be true but the results can cause it to be rejected. In accepting or rejecting H 0 , two types of error may be made. If H 0 is rejected when, in fact, it is true a type 1 error has been committed. If Ho is not true and the test fails to reject it, a type 2 error has been made.

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“ Research in the field, through study of disease as it manifests itself in nature, is an important and independent approach to solution of medical problems. Modern medical progress has been so thoroughly associated with research in the biological laboratory, and it has been so largely a development of the experimental method, that this other and older method has come in recent years to be overshadowed ” (Gordon, 1950)

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Wobeser, G.A. (1994). Formulating and Testing Hypotheses. In: Investigation and Management of Disease in Wild Animals. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5609-8_6

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Problem Identification and Hypothesis Formulation in Research

Introduction.

The term " identification of research problem " refers to the knowledge of a persistent social issue, a social phenomenon, or a notion that merits investigation in order to be understood. Such a study problem is discovered by the researcher by observation, knowledge, wisdom, and abilities.

Finding a subject to study can be difficult, not because there aren't any problems that could be researched, but because it can be difficult to formulate a problem that is both academically important and researchable and that is also original and doesn't just repeat previous research. Consider these sources of inspiration to help you decide on a problem to base your research project around.

Deductions from Theory

This relates to deductions from social philosophy or generalizations that the researcher is familiar with in life and society. Through research , these deductions from human behavior are then placed within an empirical frame of reference. A theory can be used to develop a research problem or hypothesis that states the expected results in specific empirical situations. The study asks that what relationship between variables will be observed if theory accurately summarizes the situation. Thus, the hypothesis or a theory, can then be tested using a systematic investigation.

Perspectives from Various Disciplines

Identifying a problem that will serve as the foundation for a research study can come from academic movements and scholarship that originate in disciplines other than your primary field of study. This can be a mentally stimulating activity. Examining research from related disciplines that can reveal new avenues of exploration and analysis should be included in a review of relevant literature. An interdisciplinary approach to selecting a research problem allows for a more comprehensive understanding of a very complex issue than any single discipline could provide.

Practitioner Interviews

Formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice can lead to the identification of research problems about specific topics. Discussions with experts in the field, such as teachers, social workers, health care providers, lawyers, business leaders, and so on, provide an opportunity to identify practical, "real world" issues which is often ignored within academic circles. This approach also provides some practical knowledge that may aid in the design and execution of your study.

Related Literature

A thorough review of relevant research related to your overall area of interest can help you choose a research problem. This may reveal where there are gaps in understanding or where an issue has been understudied. Research may be conducted to: 1) fill such knowledge gaps; 2) assess whether the methodologies used in previous studies can be adapted to solve other problems; or 3) determine whether a similar study could be conducted in a different subject area, in a different context, or with a different study sample.

Formulation of Research Questions/ Statement

A strong problem statement starts by outlining the broad topic on which your study is focused before guiding the reader toward the more specific problems you are looking into. A good research problem should have the following characteristics, albeit it need not be long:

1. Captivating Subject

The problem you choose should be one that inspires you to solve it; nevertheless, pursuing a research project out of mere curiosity is not recommended as this does not suggest significance. The issue you decide to research must matter to you, but it must also matter to your readers and the greater academic and/or social community that might be affected by the findings of your investigation.

2. Accepts Multiple Points of View

The issue must be phrased in a way that avoids dichotomies and instead encourages the generation and exploration of multiple points of view. A general rule of thumb in the social sciences is that a good research problem is one that will elicit a wide range of opinions from a diverse group of reasonable people.

3. Research ability

Research ability is an important aspect of creating a good research statement. It seems a smidgen obvious, but you don't want to find yourself in the middle of investigating a complex research project and realize that it is not necessary much prior research to draw from for the analysis. There's nothing wrong with original research, but as a researcher you certainly need to select the problems of research is supposed to be able in supporting, to some extent, the resources available to the researcher.

Analytical questions that are well-developed can focus on any of the following:

Draws attention to a genuine quandary, area of ambiguity, or point of confusion about a topic that is open to interpretation by your readers;

It gives birth to an answer that is unexpected and not apparent slightly but is inevitable and self-evident;

Provokes meaningful thought or discussion;

Increases the visibility of key ideas or concepts that may be understudied or hidden;

Research ability helps in providing the suggestions to the need for complex analysis or argument rather than a basic description or summary;

Process of Problem Identification in Research

The process is illustrated in the following diagram.

Features of a research questions

The research question should be feasible that is to say adequate number of subjects, adequate technical expertise, affordable in time and money, manageable in scope.

It should be interesting: Getting the answer intrigues the investigator and her friends.

It should be novel: confirms, refutes or extends previous findings, provides new findings., it should be ethical: amenable to a study that institutional review board will approve., it should be relevant: to scientific, knowledge, to clinical and health policy and to future research., definitions of hypothesis.

Etymologically speaking, hypothesis is made up of two words. Here, 'Hypo' means   an assumption or tentative or subject to verification, and 'Thesis' means a statement about a problem's solution i.e. a tentative thesis waited to be tested. The definition of hypothesis is a tentative statement about how to solve a problem. The simplest definition of hypothesis is "It is a solution to a problem that is empirically and rationally verifiable. In another word it is also defined as a hypothesis is made up of two words - 'Hypo' means a combination of two or more variables that must be verified. The term 'thesis' refers to the position of these variables in a specific frame of reference. The term hypothesis has this operational meaning.

In a more comprehensive way, a hypothesis is an educated guess about the relationship between two or more variables. A hypothesis is a specific, testable prediction/guess about what will happen in the upcoming research. The basic requirement is the hypothesis must include three components in order to be complete: the variables, the population, and the relationship between the variables. Keep in mind that a hypothesis does not have to be correct. The hypothesis predicts what the researchers expect to see, but the goal of research is to determine whether this guess is correct or incorrect.

What is an Assumption and Postulate? How are they related to hypothesis?

Assumption is the act of taking something for granted in order to simplify a situation for logical procedure. Assumptions, unlike postulates, are not the foundation of our activity. They merely facilitate the progression of an agreement by introducing restrictive conditions. Statistics and measurement formulas, for example, are based on a number of assumptions. Assumption refers to the requirement of certain conditions before an argument can be considered valid. Assumptions are made based on logical insight, and their veracity can be determined using data or evidence. The postulates are the foundation and starting point of an argument, whereas assumptions are a matter of choice and less use, giving them more freedom.

Postulates are the fundamental beliefs that strengthen most scientific activity. A postulate is a statement that is assumed to be true without any kind of proof. A postulate is an assumption we make about the relationship of two objects. For example, we could assert that a+b = b+a. This simply states that if we combine two objects, a and b, the order in which they are combined has no effect on the outcome. Other statements, known as theorems, are derived through logical deductions. We are entirely within the realm of ideas, from postulates to theorems. It is pointless to demand experimental proof of deductions. A request of this nature would be meaningless. The only appropriate appeal for proof is entirely within the realm of logic.

A hypothesis is not the same as either of these. The investigator seeks to prove a presumptive statement of a proposition. It's a shortened generalization. This generalization necessitates knowledge of fundamental principles or essential characteristics that apply to an entire class of phenomena. The theory is known as a hypothesis when it is stated formally and clearly as a testable proposition and is subjected to empirical or experimental verification. The hypothesis serves as the foundation for the entire investigation and must be validated by facts. The hypothesis is founded on some prior theory and reasoning, whereas postulates are assumed to be true. An assumption is a major problem's assumed solution. It could be partially correct.

What is the actual nature of a hypothesis?

The hypothesis is a concise statement of what will be investigated. It should be specified prior to conducting research and openly stated in the results report.

a.        This allows you to - Identify... the research objectives;

b.       The key abstract concepts involved in the research;

c.        The relationship between the problem statement and the literature review.

What are the main features of a hypothesis?

The major and common features of a hypothesis can be listed as follows

a.        It is of a conceptual nature.

b.       It is a declarative statement made verbally.

c.        It possesses the empirical referent.

d.       It denotes a possible relationship between two or more variables.

e.        It is a powerful tool for knowledge advancement that is consistent with existing knowledge and conducive to further investigation.

f.        It is testable, verifiable, and falsifiable.

g.       It is not a moral or ethical issue.

h.       It's neither too specific nor too broad.

i.         It is a prediction of outcomes.

j.         Even if proven false, it is considered valuable.

What are the roles and functions of hypothesis?

In empirical or socio-legal research, a hypothesis, which is a provisional formulation, plays an important role. It not only guides research in the right direction, but it also helps to test or suggest theories and describe a social or legal phenomenon. The roles and functions of a hypothesis can be listed as follows:

The role of hypothesis in research navigation

A hypothesis, regardless of its source, expresses what a researcher is looking for. It also offers some plausible explanations for the possible relationships between the concepts or variables mentioned. In fact, it guides you through the research. Without it, no further steps in empirical or non-doctrinal legal research are possible. A hypothesis assists the researcher in reaching "meaningful conclusions" based on "relevant" empirical data.

A hypothesis becomes supportive and helps the researcher in many respects such as it gives the idea to the type of data that must be collected in order to answer the research problem. In the same line it provides the ways to the most efficient and meaningful way to organize the data; and helps in deciding the types of methods that can be used to analyze the data.

The role of the 'tested' hypothesis: In order to draw conclusions about the initially posited relationship between the variables indicated in the hypothesis, it must be empirically tested. As a result, when empirically tested (or not), the previously assumed relationship between concepts or variables, as the case may be, becomes a proven fact. Once a hypothesis is proven, it is no longer a hypothesis.

A hypothesis, even if related to an existing theory, may, when tested, reveal certain 'facts' that are not related to the existing theory or reveal relationships other than those stated in the theory. It does not support the existing theory but rather proposes a new one.

A hypothesis can also be used to describe something. When a hypothesis is empirically tested, it tells us something about the phenomenon with which it is associated. If the hypothesis is empirically supported, our understanding of the phenomenon grows.

The hypotheses functions a significant role mainly in the scientific studies.

For example

·          It helps in the testing of the theories.

·          It serves as a great platform in the investigation activities.

·          It provides guidance to the research work or study.

·          It sometimes also suggests the theories.

·          It aids in understanding the data's requirements.

·          Explains social phenomena and advances the theory.

·          Also serves as a link between theory and investigation.

·          Provides a relationship between phenomena in such a way that empirical testing of the relationship is possible.

·          Aids in determining the most appropriate analysis technique.

·          Aids in the selection of the most appropriate type of research.

·          Provides information on the necessary data sources.

·          Under the guidance of the hypothesis, research becomes more focused.

·          It is extremely useful in conducting an investigation into a specific activity.

·          If correctly drawn, it aids in reaching conclusions.

According to Mac Ashan the hypothesis in research has mainly five functions:

1. It is a temporary solution of a problem concerning with some truth which enables an investigator to start his/her research works.

2. It offers a basis in establishing the specifics what to study for and may provide possible solutions to the problem.

3. Each hypothesis may lead to formulate another hypothesis.

4. A preliminary hypothesis may take the shape of final hypothesis.

5. It provides the investigator with definite statement which may be objectively tested and accepted or rejected and leads for interpreting results and drawing conclusions that is related to original purpose.

Importance of Hypothesis

The importance of hypothesis is understood as the eye of the researcher because it actually opens the vision to the researcher.

The main importance of hypothesis is to focus on the research.

Hypothesis helps in linking the similar facts, ideas and opinion together.

There is always a risk that without proper hypothesis, the researcher may go ahead as a blind man on the way.

Hypothesis simply plays a beautiful role like a guiding light in the entire research process.

  Characteristics of a good hypothesis

A good hypothesis should possess the various features as follows:

It is as in statement form but not in a question form.

It may be right or wrong but should be empirically tested.

It should be specific and precise.

It should not be contradictory.

It clearly mentions the independent and dependent variables which are to be compared.

It should deal with only one issue either in descriptive form or relational form.

According to C R Kothari & Gaurav   Garg (2019) the brief introduction and characteristics of research hypothesis as follows:

Research hypothesis is a predictive statement, capable of being tested by scientific methods, that relates an independent variable to some dependent variables.

Students who receive counseling will show a greater increase in creativity than students not receiving counseling.

The automobiles A is performing as well as automobile B.

The basic characteristics of hypothesis are:

Hypothesis should be clear and precise.

Hypothesis should be capable of being tested.

Hypothesis should state relationship between variables.

Hypothesis should be limited in its scope.

Hypothesis should be consistent with most known facts.

Hypothesis must explain the facts that gave rise to the need for explanation.

Ranjit Kumar (2014) in his book Research Methodology A step-by-step guide for beginners has mentioned that a hypothesis construction is the second important consideration in the formulation of a research problem in quantitative research. He further says, in epidemiological studies, to narrow the field of investigation, it is important to formulated hypotheses. The importance of hypotheses lies in their ability to bring direction, specificity and focus to a research study.

A hypothesis is a hunch, assumption, suspicion, assertion or an idea about a phenomenon, relationship or situation, the reality or truth of which you do not know.

H.K. Dangi and Shruti Dewen (2016) in their book entitled 'Business Research Methods' clearly distinguish the concept of propositions and hypothesis. Propositions are statements that define the relationships amongst the concepts. Prepositions can be judged as true or false if they are related to observable phenomena. Once a proposition can be tested for its validity then it is called a hypothesis.

Hypothesis are formulated to be tested. Hypothesis testing is a process of testing a hypothesis about a parameter of a population. Hypothesis testing involves checking the likelihood of claims regarding the population being true.

The steps of hypothesis testing according to them are illustrated as in the following diagram.

The  common types of hypothesis are null hypothesis and alternate hypothesis/research hypothesis. The null means there is no effect/impact/relation/difference between the independent variable and dependent variable whereas alternate hypothesis is also called research hypothesis. In alternate hypothesis the researcher sees or assumes the impact/effect/relation/difference between or among the independent and dependent variables.

The null hypothesis is indicated by H0 whereas alternate hypothesis is indicated by H1.

The idea of null and alternate hypothesis can be beautifully illustrated with the following examples.

H0: There is no relationship between working conditions and job satisfaction of employees.

H1: Increasing the improvement in job quality will improve the job satisfaction.

H0: There is no difference in educational level of employee to their work performance in an organization.

H1: Higher educational qualification contributes high level of work performance in an organization.

H0: There is no relation between earning and saving.

H1: Earning and saving are positively related.

Some Scholars also have classified hypothesis into simple, complex, directional, non-directional, associative, causal, inductive and deductive as well.

Simple Hypothesis

Simple hypothesis is one which deals with the only one independent variable to one dependent variable there is a direct relation or impact between them. For example The impact of education in work performance.

Complex Hypothesis

Complex hypothesis purposes and predicts the relation between two or more independent variables and two or more dependent variables. It is called complex in the sense that there is not direct and one to one relation or impact between them. For example, The training and hard work (IV) have positive impacts on individual growth as well as the goodwill of organization (DV).

Directional Hypothesis

It predicts the outcome or impact is as intellectually directed. The effect or impact or relationship between two variables into a specified direction. The researcher not only predicts the relationship but also the nature of the relation i.e. the direction. For example, Discipline as well as rules and regulation has negative relation to the creative outcome among the students.

Non-directional Hypothesis

This hypothesis predicts the relation between two variables but the nature and direction of relationship is not specified. For example 'There is a relationship between discipline and creative outcome of the school children'.

Associative Hypothesis

There is relationship between Independent Variable (IV) and Dependent Variable (DV) where when one variable changes there is the change in another variable but it is not in case of cause and effect.

Inductive and Deductive Variable

These both inductive and deductive are based on a particular type of reasoning if the hypothesis is based on deduction it is called deductive and in the same way when the researcher goes from one specific to theory then it is called as inductive variable. In this way, inductive hypotheses are formed through inductively reasoning from many specific observations to tentative explanations. The deductive one is generated through deductive reasoning based on implications of theory.

Null Hypothesis

This is a hypothesis purposes that there is no relationship or difference i.e. relationship is null between two variables. This is the conventional approach to making a prediction. It involves a statement that the researcher compares on a certain variable. The hypothesis may also state that there is no significant difference when different groups/sets are compared accordance to a specified variable. For example, ‘There is no difference in the job performance of commercial bank's employees who participate in motivational classes and those who do not participate in such classes’ is a null hypothesis. It asserts that there is no true difference in the sample statistic and population parameter under consideration and that the difference found is accidental arising out of fluctuations of sampling.

Alternative/ Research Hypothesis

As opposite to null hypothesis, research hypothesis assumes, predicts and expects the relation between independent and dependent variables.

The alternative hypothesis is a statement of what a hypothesis test attempts to establish. Alternative hypothesis is designated by: H1 or Ha. It is opposite of Null Hypothesis. It is only reached if Ha is rejected.   Frequently “alternative” is actual desired conclusion of the researcher.

It is important to see the following formula and example to comprehend the context and situation of hypothesis in relation to null/alternative.

Ha= the males go for eating out than females.

Ho= the males and females do not differ in respect of the frequency of eating out. So, Alternative hypothesis is usually the one which one wishes to prove and the Null hypothesis is the one which one wishes to disapprove.

Problem identification and hypothesis formulation in research has a significant role. This is one of the important aspect or step of the entire research process. The researcher has to do the literature review based on his/her need, interest and ability that in which areas/topic are dealt. It is not an overnight job to identify the research problem as well as formulation of hypothesis. If the process of problem identification and hypothesis formulation is systematic and objective then the entire research process and activities go to the specified direction.

Timilsena (2022). A platform for discussion to University Students- Business Research Methodology

Kumar, R (2014). Research Methodology: A step by step guide for beginners- Sage

Cooper D, Schindler PS & Sharma JK (2014) Business Research Methods-Mc Graw Hill Education

Chawla D and Sondhi N (2018) Research Methodology: Concepts and Cases- Vikas

Dangi HK & Dewen Shruit (2016). Business Research Methods-Cengave

Flick, U (2011). Introducing Research Methodology-Sage

Pant PR (1975). Social Science Research and Thesis Writing

Related Article

1. Introduction to Business Research- Fundamentals of Research-Useful for MBA Students and Professionals 2.  Report Writing: What, How & Why

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Challenges in hypothesis formulation: to reject or accept?

A hypothesis starts out with a researcher having initial hunches with he/she attempting to answer a specific research question. Watson (n.d. cited Bryman and Bell, 2011) and Newby, 2010 defines a hypothesis as a testing of the possible relationship between two or more variables in order to answer a research speculation. To accept or to reject a hypothesis is the criteria that circulate around the quantitative style of research (Tahir, n.d.), while probabilities and likelihoods are at the centre of the decision process when accepting or rejecting a hypothesis (Newby, 2010) based on the evidence reflected by the data representing the initial research question. Some of the general challenges a researcher may face in the beginning of crafting their hypothesis are how to phrase and formulate questions to answer your hypothesis, especially for an unseasoned researcher. Bryman and Bell (2011) encourage researchers to refer to other journal articles, dissertations and researchers who have carried out research to answer similar questions, and use them as a guide to formulate your hypothesis. However, the author views this as a minor challenge, and tougher challenges may emerge throughout the process of accepting a hypothesis.

The qualitative style of research consists of many decisions that have to be made, thus creating a high probability for mistakes or errors. Ghanem (2003) proposes researchers follow the mechanism model when leading to the decision of accepting or rejecting a hypothesis, which includes three basic steps to minimise these errors. The first step is hypothesis formulation — where the aim of this stage is to “produce a proposed scientific hypothesis as a tentative explanation to the phenomenon in question” (ibid); followed by hypotheses evaluation stage — where researchers may reconsider and develop alternative hypothesis is the working hypotheses may not be suitable when tested; the last step is the hypothesis verification stage — this phase aims for the clarification of the final hypothesis which is done by carrying out either or combined of these three scientific methods: research, observation or experimenting.

While the general flow for formulating hypotheses using the hypothetico-deductive approach is very similar. The author postulates that this step may be comparable or synonymous to the verification stage in the mechanism model. The last step in the hypothetico-deductive approach suggests that although a positively tested hypothesis is more enticing a negative finding of a hypothesis may still be worth the effort during the testing of the hypothesis (Fisher, 2010). However, the author would recommend researchers to be very certain about their findings before concluding their findings as a negative result, as it could lead to two potential errors. Type error 1 — which is the discarding of the false negative result, and type error 2 — which is when a false hypothesis is accepted (ibid). The author analyses that this is one of the harder challenges when formulating a hypothesis. When will a researcher be able to identify if a negative result is false? Moreover, if a researcher does not establish a hypothesis as false, and accept the hypothesis, the whole research is jeopardised. Therefore, the author fears that drawing the wrong conclusion may be one of the biggest challenges. In addition, not all researchers may have time to redesign a hypothesis due to time and capability, for example a Master’s dissertation (Fisher, 2010). The author postulates this issue may arise due to the relationship between variables, which may be more complicated than expected. While there are obstacles to face when verifying hypothesis, there are other challenges to face in the formulation stage of the mechanism model.

Ghanem (2003) suggests that one way to minimise the probability of rejecting a hypothesis relates back to the sampling method. For example, if there were 300 couples on a vacation holiday to provide a researcher with the information on booking platforms, each couple should be given the same 1 in 300 chance of providing the researcher with information. This randomness reduces the risk of bias, therefore resulting in more accurate data. The author draws the connection that supports the previous chapter in false hypothesis. The author suggests that although bias may work in favour of data aligning to the hypothesis desired by the researcher, this breaches research ethics and may result in producing a false hypothesis. This preventive step may help to avert accepting “false” hypothesis. Moreover, Newby (2010) support Ghanem, stating that obtaining poor data may be one of the difficulties that a researcher may face, especially when the researcher will draw conclusions from the analysis collected. One way to counter this is to pay attention to the method of data collection (Ghanem, 2003; Newby, 2010). Even if the researcher has chosen the most appropriate sample size and method, the sample could still be imbalanced. For instance, it a questionnaire contains sensitive questions; the sample may falsify the results and/or refuse to answer that particular question. One method to counter this issue is to be very careful in phrasing and constructing the questions in the questionnaire, and ensuring the questions are diplomatic and inoffensive.

Quantitative research appears very circumstantial. As hypothesis is the testing of possible relationships, Newby (2010) suggests “the nature of proof is the second issue that makes quantitative research distinctive”. The author agrees with this statement, when formulating a hypothesis, how would a researcher really know if the patterns we draw upon really exist? How do researchers prove to fellow academics that the findings are true? Perhaps the only possible process of validating a hypothesis is through many rounds trial and error. A researcher has to look at many aspects before accepting or rejecting hypotheses.

References: Bryman, A. and Bell, E. (2011) Business Research Methods. 3rd ed. Oxford: Oxford University Press.

Fisher, C. (2010) Researching And Writing A Dissertation: An Essential Guide For Business Students. 3rd ed. England: Pearson Education Limited.

Ghanem, T. (2003) The Process of Formulating Hypotheses and Students’ Difficulties of Hypotheses Formulation in Science Learning. Available from: http://www.academia.edu/10156442/The_Processes_of_Formulating_Hypotheses [Accessed 3 December 2015].

Marshall, C. and Rossman, G. B. (2011) Designing Qualitative Research. 5th ed. Los Angeles: SAGE Publications.

Tahir, S. Z. B. (n.d.) Hypothesis Formulation. Available from: http://www.academia.edu/8665107/HYPOTHESIS_FORMULATION [Accessed 4 December 2015].

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Describe the sources and problems in formulation of hypothesis

The Sources of Formulation of a Hypothesis :

Problems in the formulation of useful hypothesis .

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Define the concepts of 'evaluation', 'measurement' and 'assessment' And also explain the differences among them with examples

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