importance formulating a hypothesis

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• Indian J Anaesth
• v.63(8); 2019 Aug

Formulating a good research question: Pearls and pitfalls

Wilson fandino.

Guys' and St Thomas' Hospital National Health Service Foundation Trust, London, United Kingdom

The process of formulating a good research question can be challenging and frustrating. While a comprehensive literature review is compulsory, the researcher usually encounters methodological difficulties in the conduct of the study, particularly if the primary study question has not been adequately selected in accordance with the clinical dilemma that needs to be addressed. Therefore, optimising time and resources before embarking in the design of a clinical protocol can make an impact on the final results of the research project. Researchers have developed effective ways to convey the message of how to build a good research question that can be easily recalled under the acronyms of PICOT (population, intervention, comparator, outcome, and time frame) and FINER (feasible, interesting, novel, ethical, and relevant). In line with these concepts, this article highlights the main issues faced by clinicians, when developing a research question.

INTRODUCTION

What is your research question? This is very often one of the first queries made by statisticians, when researchers come up with an interesting idea. In fact, the findings of a study may only acquire relevance if they provide an accurate and unbiased answer to a specific question,[ 1 , 2 ] and it has been suggested that up to one-third of the time spent in the whole process—from the conception of an idea to the publication of the manuscript—could be invested in finding the right primary study question.[ 3 ] Furthermore, selecting a good research question can be a time-consuming and challenging task: in one retrospective study, Mayo et al . reported that 3 out of 10 articles published would have needed a major rewording of the question.[ 1 ] This paper explores some recommendations to consider before starting any research project, and outlines the main difficulties faced by young and experienced clinicians, when it comes time to turn an exciting idea into a valuable and feasible research question.

OPTIMISATION OF TIME AND RESOURCES

Focusing on the primary research question.

The process of developing a new idea usually stems from a dilemma inherent to the clinical practice.[ 2 , 3 , 4 ] However, once the problem has been identified, it is tempting to formulate multiple research questions. Conducting a clinical trial with more than one primary study question would not be feasible. First, because each question may require a different research design, and second, because the necessary statistical power of the study would demand unaffordable sample sizes. It is the duty of editors and reviewers to make sure that authors clearly identify the primary research question, and as a consequence, studies approaching more than one primary research question may not be suitable for publication.

Working in the right environment

Teamwork is essential to find the appropriate research question. Working in the right environment will enable the investigator to interact with colleagues with different backgrounds, and create opportunities to exchange experiences in a collaborative way between clinicians and researchers. Likewise, it is of paramount importance to get involved colleagues with expertise in the field (lead clinicians, education supervisors, research mentors, department chairs, epidemiologists, biostatisticians, and ethical consultants, among others), and ask for their guidance.[ 5 , 6 , 7 , 8 ]

Evaluating the pertinence of the study

The researcher should wonder if, on the basis of the research question formulated, there is a need for a study to address the problem, as clinical research usually entails a large investment of resources and workforce involvement. Thus, if the answer to the posed clinical question seems to be evident before starting the study, investing in research to address the problem would become superfluous. For example, in a clinical trial, Herzog-Niescery et al . compared laryngeal masks with cuffed and uncuffed tracheal tubes, in the context of surgeons' exposure to sevoflurane, in infants undergoing adenoidectomy. However, it appears obvious that cuffed tracheal tubes are preferred to minimise surgeons' exposure to volatile gases, as authors concluded after recruiting 60 patients.[ 9 ]

Conducting a thorough literature review

Any research project requires the identification of at least one of three problems: the evidence is scarce, the existing literature yields conflicting results, or the results could be improved. Hence, a comprehensive review of the topic is imperative, as it allows the researcher to identify this gap in the literature, formulate a hypothesis and develop a research question.[ 2 ] To this end, it is crucial to be attentive to new ideas, keep the imagination roaming with reflective attitude, and remain sceptical to the new-gained information.[ 4 , 7 ]

Narrowing the research question

A broad research question may encompass an unaffordable extensive topic. For instance, do supraglottic devices provide similar conditions for the visualization of the glottis aperture in a German hospital? Such a general research question usually needs to be narrowed, not only by cutting away unnecessary components (a German hospital is irrelevant in this context), but also by defining a target population, a specific intervention, an alternative treatment or procedure to be compared with the intervention, a measurable primary outcome, and a time frame of the study. In contrast, an example of a good research question would be: among children younger than 1 year of age undergoing elective minor procedures, to what extent the insertion times are different, comparing the Supreme™ laryngeal mask airway (LMA) to Proseal™ LMA, when placed after reaching a BIS index <60?[ 10 ] In this example, the core ingredients of the research question can be easily identified as: children <1 year of age undergoing minor elective procedures, Supreme™ LMA, Proseal™ LMA and insertion times at anaesthetic induction when reaching a BIS index <60. These components are usually gathered in the literature under the acronym of PICOT (population, intervention, comparator, outcome and time frame, respectively).[ 1 , 3 , 5 ]

PICOT FRAMEWORK

Table 1 summarises the foremost questions likely to be addressed when working on PICOT frame.[ 1 , 6 , 8 ] These components are also applicable to observational studies, where the exposure takes place of the intervention.[ 1 , 11 ] Remarkably, if after browsing the title and the abstract of a paper, the reader is not able to clearly identify the PICOT parameters, and elucidate the question posed by the authors, there should be reasonable scepticism regarding the scientific rigor of the work.[ 12 , 13 ] All these elements are crucial in the design and methodology of a clinical trial, as they can affect the feasibility and reliability of results. Having formulated the primary study question in the context of the PICOT framework [ Table 1 ],[ 1 , 6 , 8 ] the researcher should be able to elucidate which design is most suitable for their work, determine what type of data needs to be collected, and write a structured introduction tailored to what they want to know, explicitly mentioning the primary study hypothesis, which should lead to formulate the main research question.[ 1 , 2 , 6 , 8 ]

Key questions to be answered when working with the PICOT framework (population, intervention, comparator, outcome, and time frame) in a clinical research design

Occasionally, the intended population of the study needs to be modified, in order to overcome any potential ethical issues, and/or for the sake of convenience and feasibility of the project. Yet, the researcher must be aware that the external validity of the results may be compromised. As an illustration, in a randomised clinical trial, authors compared the ease of tracheal tube insertion between C-MAC video laryngoscope and direct laryngoscopy, in patients presenting to the emergency department with an indication of rapid sequence intubation. However, owing to the existence of ethical concerns, a substantial amount of patients requiring emergency tracheal intubation, including patients with major maxillofacial trauma and ongoing cardiopulmonary resuscitation, had to be excluded from the trial.[ 14 ] In fact, the design of prospective studies to explore this subset of patients can be challenging, not only because of ethical considerations, but because of the low incidence of these cases. In another study, Metterlein et al . compared the glottis visualisation among five different supraglottic airway devices, using fibreroptic-guided tracheal intubation in an adult population. Despite that the study was aimed to explore the ease of intubation in patients with anticipated difficult airway (thus requiring fibreoptic tracheal intubation), authors decided to enrol patients undergoing elective laser treatment for genital condylomas, as a strategy to hasten the recruitment process and optimise resources.[ 15 ]

Intervention

Anaesthetic interventions can be classified into pharmacological (experimental treatment) and nonpharmacological. Among nonpharmacological interventions, the most common include anaesthetic techniques, monitoring instruments and airway devices. For example, it would be appropriate to examine the ease of insertion of Supreme™ LMA, when compared with ProSeal™ LMA. Notwithstanding, a common mistake is the tendency to be focused on the data aimed to be collected (the “stated” objective), rather than the question that needs to be answered (the “latent” objective).[ 1 , 4 ] In one clinical trial, authors stated: “we compared the Supreme™ and ProSeal™ LMAs in infants by measuring their performance characteristics, including insertion features, ventilation parameters, induced changes in haemodynamics, and rates of postoperative complications”.[ 10 ] Here, the research question has been centered on the measurements (insertion characteristics, haemodynamic variables, LMA insertion characteristics, ventilation parameters) rather than the clinical problem that needs to be addressed (is Supreme™ LMA easier to insert than ProSeal™ LMA?).

Comparators in clinical research can also be pharmacological (e.g., gold standard or placebo) or nonpharmacological. Typically, not more than two comparator groups are included in a clinical trial. Multiple comparisons should be generally avoided, unless there is enough statistical power to address the end points of interest, and statistical analyses have been adjusted for multiple testing. For instance, in the aforementioned study of Metterlein et al .,[ 15 ] authors compared five supraglottic airway devices by recruiting only 10--12 participants per group. In spite of the authors' recommendation of using two supraglottic devices based on the results of the study, there was no mention of statistical adjustments for multiple comparisons, and given the small sample size, larger clinical trials will undoubtedly be needed to confirm or refute these findings.[ 15 ]

A clear formulation of the primary outcome results of vital importance in clinical research, as the primary statistical analyses, including the sample size calculation (and therefore, the estimation of the effect size and statistical power), will be derived from the main outcome of interest. While it is clear that using more than one primary outcome would not be appropriate, it would be equally inadequate to include multiple point measurements of the same variable as the primary outcome (e.g., visual analogue scale for pain at 1, 2, 6, and 12 h postoperatively).

Composite outcomes, in which multiple primary endpoints are combined, may make it difficult to draw any conclusions based on the study findings. For example, in a clinical trial, 200 children undergoing ophthalmic surgery were recruited to explore the incidence of respiratory adverse events, when comparing desflurane with sevoflurane, following the removal of flexible LMA during the emergence of the anaesthesia. The primary outcome was the number of respiratory events, including breath holding, coughing, secretions requiring suction, laryngospasm, bronchospasm, and mild desaturation.[ 16 ] Should authors had claimed a significant difference between these anaesthetic volatiles, it would have been important to elucidate whether those differences were due to serious adverse events, like laryngospasm or bronchospasm, or the results were explained by any of the other events (e.g., secretions requiring suction). While it is true that clinical trials evaluating the occurrence of adverse events like laryngospasm/bronchospasm,[ 16 , 17 ] or life-threating complications following a tracheal intubation (e.g., inadvertent oesophageal placement, dental damage or injury of the larynx/pharynx)[ 14 ] are almost invariably underpowered, because the incidence of such events is expected to be low, subjective outcomes like coughing or secretions requiring suction should be avoided, as they are highly dependent on the examiner's criteria.[ 16 ]

Secondary outcomes are useful to document potential side effects (e.g., gastric insufflation after placing a supraglottic device), and evaluate the adherence (say, airway leak pressure) and safety of the intervention (for instance, occurrence, or laryngospasm/bronchospasm).[ 17 ] Nevertheless, the problem of addressing multiple secondary outcomes without the adequate statistical power is habitual in medical literature. A good illustration of this issue can be found in a study evaluating the performance of two supraglottic devices in 50 anaesthetised infants and neonates, whereby authors could not draw any conclusions in regard to potential differences in the occurrence of complications, because the sample size calculated made the study underpowered to explore those differences.[ 17 ]

Among PICOT components, the time frame is the most likely to be omitted or inappropriate.[ 1 , 12 ] There are two key aspects of the time component that need to be clearly specified in the research question: the time of measuring the outcome variables (e.g. visual analogue scale for pain at 1, 2, 6, and 12 h postoperatively), and the duration of each measurement (when indicated). The omission of these details in the study protocol might lead to substantial differences in the methodology used. For instance, if a study is designed to compare the insertion times of three different supraglottic devices, and researchers do not specify the exact moment of LMA insertion in the clinical trial protocol (i.e., at the anaesthetic induction after reaching a BIS index < 60), placing an LMA with insufficient depth of anaesthesia would have compromised the internal validity of the results, because inserting a supraglottic device in those patients would have resulted in failed attempts and longer insertion times.[ 10 ]

FINER CRITERIA

A well-elaborated research question may not necessarily be a good question. The proposed study also requires being achievable from both ethical and realistic perspectives, interesting and useful to the clinical practice, and capable to formulate new hypotheses, that may contribute to the generation of knowledge. Researchers have developed an effective way to convey the message of how to build a good research question, that is usually recalled under the acronym of FINER (feasible, interesting, novel, ethical and relevant).[ 5 , 6 , 7 ] Table 2 highlights the main characteristics of FINER criteria.[ 7 ]

Main features of FINER criteria (Feasibility, interest, novelty, ethics, and relevance) to formulate a good research question. Adapted from Cummings et al .[ 7 ]

Novelty and relevance

Although it is clear that any research project should commence with an accurate literature interpretation, in many instances it represents the start and the end of the research: the reader will soon realise that the answer to several questions can be easily found in the published literature.[ 5 ] When the question overcomes the test of a thorough literature review, the project may become novel (there is a gap in the knowledge, and therefore, there is a need for new evidence on the topic) and relevant (the paper may contribute to change the clinical practice). In this context, it is important to distinguish the difference between statistical significance and clinical relevance: in the aforementioned study of Oba et al .,[ 10 ] despite the means of insertion times were reported as significant for the Supreme™ LMA, as compared with ProSeal™ LMA, the difference found in the insertion times (528 vs. 486 sec, respectively), although reported as significant, had little or no clinical relevance.[ 10 ] Conversely, a statistically significant difference of 12 sec might be of clinical relevance in neonates weighing <5 kg.[ 17 ] Thus, statistical tests must be interpreted in the context of a clinically meaningful effect size, which should be previously defined by the researcher.

Feasibility and ethical aspects

Among FINER criteria, there are two potential barriers that may prevent the successful conduct of the project and publication of the manuscript: feasibility and ethical aspects. These obstacles are usually related to the target population, as discussed above. Feasibility refers not only to the budget but also to the complexity of the design, recruitment strategy, blinding, adequacy of the sample size, measurement of the outcome, time of follow-up of participants, and commitment of clinicians, among others.[ 3 , 7 ] Funding, as a component of feasibility, may also be implicated in the ethical principles of clinical research, because the choice of the primary study question may be markedly influenced by the specific criteria demanded in the interest of potential funders.

Discussing ethical issues with local committees is compulsory, as rules applied might vary among countries.[ 18 ] Potential risks and benefits need to be carefully weighed, based upon the four principles of respect for autonomy, beneficence, non-maleficence, and justice.[ 19 ] Although many of these issues may be related to the population target (e.g., conducting a clinical trial in patients with ongoing cardiopulmonary resuscitation would be inappropriate, as would be anaesthetising patients undergoing elective LASER treatment for condylomas, to examine the performance of supraglottic airway devices),[ 14 , 15 ] ethical conflicts may also arise from the intervention (particularly those involving the occurrence of side effects or complications, and their potential for reversibility), comparison (e.g., use of placebo or sham procedures),[ 19 ] outcome (surrogate outcomes should be considered in lieu of long term outcomes), or time frame (e.g., unnecessary longer exposition to an intervention). Thus, FINER criteria should not be conceived without a concomitant examination of the PICOT checklist, and consequently, PICOT framework and FINER criteria should not be seen as separated components, but rather complementary ingredients of a good research question.

Undoubtedly, no research project can be conducted if it is deemed unfeasible, and most institutional review boards would not be in a position to approve a work with major ethical problems. Nonetheless, whether or not the findings are interesting, is a subjective matter. Engaging the attention of readers also depends upon a number of factors, including the manner of presenting the problem, the background of the topic, the intended audience, and the reader's expectations. Furthermore, the interest is usually linked to the novelty and relevance of the topic, and it is worth nothing that editors and peer reviewers of high-impact medical journals are usually reluctant to accept any publication, if there is no novelty inherent to the research hypothesis, or there is a lack of relevance in the results.[ 11 ] Nevertheless, a considerable number of papers have been published without any novelty or relevance in the topic addressed. This is probably reflected in a recent survey, according to which only a third of respondents declared to have read thoroughly the most recent papers downloaded, and at least half of those manuscripts remained unread.[ 20 ] The same study reported that up to one-third of papers examined remained uncited after 5 years of publication, and only 20% of papers accounted for 80% of the citations.[ 20 ]

Formulating a good research question can be fascinating, albeit challenging, even for experienced investigators. While it is clear that clinical experience in combination with the accurate interpretation of literature and teamwork are essential to develop new ideas, the formulation of a clinical problem usually requires the compliance with PICOT framework in conjunction with FINER criteria, in order to translate a clinical dilemma into a researchable question. Working in the right environment with the adequate support of experienced researchers, will certainly make a difference in the generation of knowledge. By doing this, a lot of time will be saved in the search of the primary study question, and undoubtedly, there will be more chances to become a successful researcher.

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Conflicts of interest.

There are no conflicts of interest.

5 Characteristics of a Good Hypothesis: A Guide for Researchers

• by Brian Thomas
• October 10, 2023

Are you a curious soul, always seeking answers to the whys and hows of the world? As a researcher, formulating a hypothesis is a crucial first step towards unraveling the mysteries of your study. A well-crafted hypothesis not only guides your research but also lays the foundation for drawing valid conclusions. But what exactly makes a hypothesis a good one? In this blog post, we will explore the five key characteristics of a good hypothesis that every researcher should know.

Here, we will delve into the world of hypotheses, covering everything from their types in research to understanding if they can be proven true. Whether you’re a seasoned researcher or just starting out, this blog post will provide valuable insights on how to craft a sound hypothesis for your study. So let’s dive in and uncover the secrets to formulating a hypothesis that stands strong amidst the scientific rigor!

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5 Characteristics of a Good Hypothesis

Clear and specific.

A good hypothesis is like a GPS that guides you to the right destination. It needs to be clear and specific so that you know exactly what you’re testing. Avoid vague statements or general ideas. Instead, focus on crafting a hypothesis that clearly states the relationship between variables and the expected outcome. Clarity is key, my friend!

Testable and Falsifiable

A hypothesis might sound great in theory, but if you can’t test it or prove it wrong, then it’s like chasing unicorns. A good hypothesis should be testable and falsifiable – meaning there should be a way to gather evidence to support or refute it. Don’t be afraid to challenge your hypothesis and put it to the test. Only when it can be proven false can it truly be considered a good hypothesis.

Based on Existing Knowledge

Imagine trying to build a Lego tower without any Lego bricks. That’s what it’s like to come up with a hypothesis that has no basis in existing knowledge. A good hypothesis is grounded in previous research, theories, or observations. It shows that you’ve done your homework and understand the current state of knowledge in your field. So, put on your research hat and gather those building blocks for a solid hypothesis!

Specific Predictions

No, we’re not talking about crystal ball predictions or psychic abilities here. A good hypothesis includes specific predictions about what you expect to happen. It’s like making an educated guess based on your understanding of the variables involved. These predictions help guide your research and give you something concrete to look for. So, put on those prediction goggles, my friend, and let’s get specific!

Relevant to the Research Question

A hypothesis is a road sign that points you in the right direction. But if it’s not relevant to your research question, then you might end up in a never-ending detour. A good hypothesis aligns with your research question and addresses the specific problem or phenomenon you’re investigating. Keep your focus on the main topic and avoid getting sidetracked by shiny distractions. Stay relevant, my friend, and you’ll find the answers you seek!

And there you have it: the five characteristics of a good hypothesis. Remember, a good hypothesis is clear, testable, based on existing knowledge, makes specific predictions, and is relevant to your research question. So go forth, my friend, and hypothesize your way to scientific discovery!

FAQs: Characteristics of a Good Hypothesis

In the realm of scientific research, a hypothesis plays a crucial role in formulating and testing ideas. A good hypothesis serves as the foundation for an experiment or study, guiding the researcher towards meaningful results. In this FAQ-style subsection, we’ll explore the characteristics of a good hypothesis, their types, formulation, and more. So let’s dive in and unravel the mysteries of hypothesis-making!

What Are Two Important Characteristics of a Good Hypothesis

A good hypothesis possesses two important characteristics:

Testability : A hypothesis must be testable to determine its validity. It should be formulated in a way that allows researchers to design and conduct experiments or gather data for analysis. For example, if we hypothesize that “drinking herbal tea reduces stress,” we can easily test it by conducting a study with a control group and a group drinking herbal tea.

Falsifiability : Falsifiability refers to the potential for a hypothesis to be proven wrong. A good hypothesis should make specific predictions that can be refuted or supported by evidence. This characteristic ensures that hypotheses are based on empirical observations rather than personal opinions. For instance, the hypothesis “all swans are white” can be falsified by discovering a single black swan.

What Are the Types of Hypothesis in Research

In research, there are three main types of hypotheses:

Null Hypothesis (H0) : The null hypothesis is a statement of no effect or relationship. It assumes that there is no significant difference between variables or no effect of a treatment. Researchers aim to reject the null hypothesis in favor of an alternative hypothesis.

Alternative Hypothesis (HA or H1) : The alternative hypothesis is the opposite of the null hypothesis. It asserts that there is a significant difference between variables or an effect of a treatment. Researchers seek evidence to support the alternative hypothesis.

Directional Hypothesis : A directional hypothesis predicts the specific direction of the relationship or difference between variables. For example, “increasing exercise duration will lead to greater weight loss.”

Can a Hypothesis Be Proven True

In scientific research, hypotheses are not proven true; they are supported or rejected based on empirical evidence . Even if a hypothesis is supported by multiple studies, new evidence could arise that contradicts it. Scientific knowledge is always subject to revision and refinement. Therefore, the goal is to gather enough evidence to either support or reject a hypothesis, rather than proving it absolutely true.

What Are the Six Parts of a Hypothesis

A hypothesis typically consists of six essential parts:

Research Question : A clear and concise question that the hypothesis seeks to answer.

Variables : Identification of the independent (manipulated) and dependent (measured) variables involved in the hypothesis.

Population : The specific group or individuals the hypothesis is concerned with.

Relationship or Comparison : The expected relationship or difference between variables, often indicated by directional terms like “more,” “less,” “higher,” or “lower.”

Predictability : A statement of the predicted outcome or result based on the relationship between variables.

Testability : The ability to design an experiment or gather data to support or reject the hypothesis.

How Do You Start a Hypothesis Sentence

When starting a hypothesis sentence, it is essential to use clear and concise language to express your ideas. A common approach is to use the phrase “If…then…” to establish the conditional relationship between variables. For example:

• If [independent variable], then [dependent variable] because [explanation of expected relationship].

This structure allows for a straightforward and logical formulation of the hypothesis.

What Are Examples of Hypotheses

Here are a few examples of well-formulated hypotheses:

If exposure to sunlight increases, then plants will grow taller because sunlight is necessary for photosynthesis.

If students receive praise for good grades, then their motivation to excel will increase because they seek recognition and approval.

If the dose of a painkiller is increased, then the relief from pain will last longer because a higher dosage has a prolonged effect.

What Are the Five Key Elements to a Good Hypothesis

A good hypothesis should include the following five key elements:

Clarity : The hypothesis should be clear and specific, leaving no room for interpretation.

Testability : It should be possible to test the hypothesis through experimentation or data collection.

Relevance : The hypothesis should be directly tied to the research question or problem being investigated.

Specificity : It must clearly state the relationship or difference between variables being studied.

Falsifiability : The hypothesis should make predictions that can be refuted or supported by empirical evidence.

What Makes a Good Hypothesis in a Research Paper

In a research paper, a good hypothesis should have the following characteristics:

Relevance : It must directly relate to the research topic and address the objectives of the study.

Clarity : The hypothesis should be concise and precisely worded to avoid confusion.

Unambiguous : It must leave no room for multiple interpretations or ambiguity.

Logic : The hypothesis should be based on rational and logical reasoning, considering existing theories and observations.

Empirical Support : Ideally, the hypothesis should be supported by prior empirical evidence or strong theoretical justifications.

Is a Hypothesis Always a Question

No, a hypothesis is not always in the form of a question. While some hypotheses can take the form of a question, others may be statements asserting a relationship or difference between variables. The form of a hypothesis depends on the research question being addressed and the researcher’s preferred style of expression.

What Are the Three Things Needed for a Good Hypothesis

For a hypothesis to be considered good, it must fulfill the following three criteria:

Testability : The hypothesis should be formulated in a way that allows for empirical testing through experimentation or data collection.

Falsifiability : It must make specific predictions that can be potentially refuted or supported by evidence.

Relevance : The hypothesis should directly address the research question or problem being investigated.

What Are the Four Components to a Good Hypothesis

A good hypothesis typically consists of four components:

Independent Variable : The variable being manipulated or controlled by the researcher.

Dependent Variable : The variable being measured or observed to determine the effect of the independent variable.

Directionality : The predicted relationship or difference between the independent and dependent variables.

Population : The specific group or individuals to which the hypothesis applies.

How Do You Formulate a Hypothesis

To formulate a hypothesis, follow these steps:

Identify the Research Topic : Clearly define the area or phenomenon you want to study.

Conduct Background Research : Review existing literature and research to gain knowledge about the topic.

Formulate a Research Question : Ask a clear and focused question that you want to answer through your hypothesis.

State the Null and Alternative Hypotheses : Develop a null hypothesis to assume no effect or relationship, and an alternative hypothesis to propose a significant effect or relationship.

Decide on Variables and Relationships : Determine the independent and dependent variables and the predicted relationship between them.

Refine and Test : Refine your hypothesis, ensuring it is clear, testable, and falsifiable. Then, design experiments or gather data to support or reject it.

What Is a Characteristic of a Hypothesis MCQ

Multiple-choice questions (MCQ) regarding the characteristics of a hypothesis often assess knowledge on the testability and falsifiability of hypotheses. They may ask about the criteria that distinguish a good hypothesis from a poor one or the importance of making specific predictions. Remember to choose answers that emphasize the empirical and testable nature of hypotheses.

What Five Criteria Must Be Satisfied for a Hypothesis to Be Scientific

For a hypothesis to be considered scientific, it must satisfy the following five criteria:

Testability : The hypothesis must be formulated in a way that allows it to be tested through experimentation or data collection.

Falsifiability : It should make specific predictions that can be potentially refuted or supported by empirical evidence.

Empirical Basis : The hypothesis should be based on empirical observations or existing theories and knowledge.

Relevance : It must directly address the research question or problem being investigated.

Objective : A scientific hypothesis should be free from personal biases or subjective opinions, focusing on objective observations and analysis.

What Are the Steps of Theory Development in Scientific Methods

In scientific methods, theory development typically involves the following steps:

Observation : Identifying a phenomenon or pattern worthy of investigation through observation or empirical data.

Formulation of a Hypothesis : Constructing a hypothesis that explains the observed phenomena or predicts a relationship between variables.

Data Collection : Gathering relevant data through experiments, surveys, observations, or other research methods.

Analysis : Analyzing the collected data to evaluate the hypothesis’s predictions and determine their validity.

Revision and Refinement : Based on the analysis, refining the hypothesis, modifying the theory, or formulating new hypotheses for further investigation.

Which of the Following Makes a Good Hypothesis

A good hypothesis is characterized by:

Testability : The ability to form experiments or gather data to support or refute the hypothesis.

Falsifiability : The potential for the hypothesis’s predictions to be proven wrong based on empirical evidence.

Clarity : A clear and concise statement or question that leaves no room for ambiguity.

Relevancy : Directly addressing the research question or problem at hand.

Remember, it is important to select the option that encompasses all these characteristics.

What Are the Characteristics of a Good Hypothesis

A good hypothesis possesses several characteristics, such as:

Testability : It should allow for empirical testing through experiments or data collection.

Falsifiability : The hypothesis should make specific predictions that can be potentially refuted or supported by evidence.

Clarity : It must be clearly and precisely formulated, leaving no room for ambiguity or multiple interpretations.

Relevance : The hypothesis should directly relate to the research question or problem being investigated.

What Is the Five-Step p-value Approach to Hypothesis Testing

The five-step p-value approach is a commonly used framework for hypothesis testing:

Step 1: Formulating the Hypotheses : The null hypothesis (H0) assumes no effect or relationship, while the alternative hypothesis (HA) proposes a significant effect or relationship.

Step 2: Setting the Significance Level : Decide on the level of significance (α), which represents the probability of rejecting the null hypothesis when it is true. The commonly used level is 0.05 (5%).

Step 3: Collecting Data and Performing the Test : Acquire and analyze the data, calculating the test statistic and the corresponding p-value.

Step 4: Comparing the p-value with the Significance Level : If the p-value is less than the significance level (α), reject the null hypothesis. Otherwise, fail to reject the null hypothesis.

Step 5: Drawing Conclusions : Based on the comparison in Step 4, interpret the results and draw conclusions about the hypothesis.

What Are the Stages of Hypothesis

The stages of hypothesis generally include:

Observation : Identifying a pattern, phenomenon, or research question that warrants investigation.

Formulation : Developing a hypothesis that explains or predicts the relationship or difference between variables.

Testing : Collecting data, designing experiments, or conducting studies to gather evidence supporting or refuting the hypothesis.

Analysis : Assessing the collected data to determine whether the results support or reject the hypothesis.

Conclusion : Drawing conclusions based on the analysis and making further iterations, refinements, or new hypotheses for future research.

What Is a Characteristic of a Good Hypothesis

A characteristic of a good hypothesis is its ability to make specific predictions about the relationship or difference between variables. Good hypotheses avoid vague statements and clearly articulate the expected outcomes. By doing so, researchers can design experiments or gather data that directly test the predictions, leading to meaningful results.

How Do You Write a Good Hypothesis Example

To write a good hypothesis example, follow these guidelines:

If possible, use the “If…then…” format to express a conditional relationship between variables.

Be clear and concise in stating the variables involved, the predicted relationship, and the expected outcome.

Ensure the hypothesis is testable, meaning it can be evaluated through experiments or data collection.

For instance, consider the following example:

If students study for longer periods of time, then their test scores will improve because increased study time allows for better retention of information and increased proficiency.

What Is the Difference Between Hypothesis and Hypotheses

The main difference between a hypothesis and hypotheses lies in their grammatical number. A hypothesis refers to a single statement or proposition that is formulated to explain or predict the relationship between variables. On the other hand, hypotheses is the plural form of the term hypothesis, commonly used when multiple statements or propositions are proposed and tested simultaneously.

What Is a Good Hypothesis Statement

A good hypothesis statement exhibits the following qualities:

Clarity : It is written in clear and concise language, leaving no room for confusion or ambiguity.

Testability : The hypothesis should be formulated in a way that enables testing through experiments or data collection.

Specificity : It must clearly state the predicted relationship or difference between variables.

By adhering to these criteria, a good hypothesis statement guides research efforts effectively.

What Is Not a Characteristic of a Good Hypothesis

A characteristic that does not align with a good hypothesis is subjectivity . A hypothesis should be objective, based on empirical observations or existing theories, and free from personal bias. While personal interpretations and opinions can inspire the formulation of a hypothesis, it must ultimately rely on objective observations and be open to empirical testing.

By now, you’ve gained insights into the characteristics of a good hypothesis, including testability, falsifiability, clarity,

• characteristics
• falsifiable
• good hypothesis
• hypothesis testing
• null hypothesis
• observations
• scientific rigor

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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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• Formulation of Hypothesis

Children who spend more time playing outside are more likely to be imaginative. What do you think this statement is an example of in terms of scientific research ? If you guessed a hypothesis, then you'd be correct. The formulation of hypotheses is a fundamental step in psychology research.

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What is a hypothesis? 

What method states that a hypothesis needs to be formulated to produce good research?

What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV, and states how it will influence the DV. 

Which type of hypothesis is also known as a two-tailed hypothesis? 

What are the requirements of a good hypothesis? 

What steps do researchers need to take when formulating a testable hypothesis? 

What is a hypothesis predicting? 

What type of hypothesis matches the following definition. A predictive statement that researchers use when it is thought that the IV will not influence the DV.

What type of hypothesis is the following example. There will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

Why are hypotheses needed in research? 

What is an operationalised variable?

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• Gibson's Theory of Direct Perception
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• Gunderson et al 2013 study
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• First, we will discuss the importance of hypotheses in research.
• We will then cover formulating hypotheses in research, including the steps in the formulation of hypotheses in research methodology.
• We will provide examples of hypotheses in research throughout the explanation.
• Finally, we will delve into the different types of hypotheses in research.

What is a Hypothesis?

The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . To be classed as scientific research , it must be observable, valid, reliable and follow a standardised procedure.

One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.

The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.

The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.

In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.

If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.

Importance of Hypothesis in Research

The purpose of including hypotheses in psychology research is:

• To provide a summary of the research, how it will be investigated, and what is expected to be found.
• To provide an answer to the research question.

When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.

Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.

The researcher then forms a research question that the researcher will attempt to answer in their study.

Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.

The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology

Researchers must follow certain steps to formulate testable hypotheses when conducting research.

Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables ? Or will it be more concerned with the correlation between variables?

All researchers will likely complete the following.

• Investigating background research in the area of interest.
• Formulating or investigating a theory.
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.

The above steps are used to formulate testable hypotheses.

The Formulation of Testable Hypotheses

The hypothesis is important in research as it indicates what and how a variable will be investigated.

The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.

This is known as the scientific method.

Formulating Hypotheses in Research

When formulating hypotheses, things that researchers should consider are:

Types of Hypotheses in Research

Researchers can propose different types of hypotheses when carrying out research.

The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression ."

The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.

The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.

In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.

An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.

The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.

The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.

The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.

Example Hypothesis in Research

To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables: the independent and the dependent.

If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.

Formulation of Hypothesis - Key Takeaways

• The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. One of the important steps in scientific research is to create a hypothesis.
• The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
• Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
• There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
• There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).

Flashcards in Formulation of Hypothesis 18

The hypothesis is a predictive, testable statement concerning the outcome/ results the researcher expects to find. 

The scientific method states that researchers need to formulate a good hypothesis before starting the research. 

Directional, alternative hypothesis 

Alternative hypothesis 

A good hypothesis should:

• identify and operationalise the independent and dependent variable
• be testable 
• be falsifiable 
• predictive statements 

All researchers will likely complete the following

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

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Frequently Asked Questions about Formulation of Hypothesis

What are the 3 types of hypotheses?

The three types of hypotheses are:

• Null hypothesis 
• Alternative hypothesis 
• Directional/non-directional hypothesis 

What is an example of a hypothesis in psychology?

An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

What are the steps in formulating a hypothesis?

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

What is formulation of hypothesis in research? 

The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.

How to formulate  null and alternative hypothesis?

When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go. 

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Understanding the importance of a research hypothesis

A research hypothesis is a specification of a testable prediction about what a researcher expects as the outcome of the study. It comprises certain aspects such as the population, variables, and the relationship between the variables. It states the specific role of the position of individual elements through empirical verification. When conducting research, there are certain assumptions that are made by the researcher. According to the available information, the goal is to present the expected outcome after testing them.

A hypothesis should be precise and accurate

A hypothesis is a clear statement of the information that the researcher intends to investigate. It is thus a clear statement that is essential before conducting research.

Based on this aspect, the features of the hypothesis are listed below:

1. Conceptual

The statement of the hypothesis is based on a certain concept i.e. it could be either related to the theory or the pre-assumption of the researcher about certain variables i.e. educated guess. This leads to linking the research questions of the study. It helps the collection of data and conducting analysis as per the stated concept.

People who shop at speciality stores tend to spend more on luxury brands as compared to those who shop at a department store.

2. Verbal statement

The research hypothesis represents a verbal statement in declarative form. The hypothesis is often stated in mathematical form. However, it brings in the possibility of representing the idea, assumption, or concept of the researcher in the form of words that could be tested.

The capability of students who are undergoing vocational training programs is not different from the students undergoing regular studies.

3. Empirical reference

By building a tentative relationship among concepts, hypothesis testing provides an empirical verification of a study. It helps validate the assumption of the researcher.

The quality of nursing education affects the quality of nursing practice skills.

4. Tentative relationship

It links the variables as per assumption and builds a tentative relationship. A hypothesis is initially unverified, therefore the relationship between variables is uncertain. Thus a predictable relationship is specified.

Sleep deprivation affects the productivity of an individual.

5. Tool of knowledge advancement

With help of a hypothesis statement, the researcher has the opportunity of verifying the available knowledge and having further enquiry about a concept. Thus, it helps the advancement of knowledge.

The effectiveness of social awareness programs influences the living standards of people.

The hypothesis statement provides the benefit of assessing the available information and making the appropriate prediction about the future. With the possibility of verifiability and identifying falsifiable information, researchers assess their assumptions and determine accurate conclusions.

People who are exposed to a high level of ultraviolet light tend to have a higher incidence of cancer.

7. Not moral

The hypothesis statement is not based on the consideration of moral values or ethics. It is as per the beliefs or assumptions of the researcher. However, testing and prediction are not entirely based on individual moral beliefs. For example, people having sample moral values would take the same strategy for business management. In this case, it is not the desired objective to study the business management strategy.

Neither too specific nor too general

A hypothesis should not be too general or too specific.

‘Actions of an individual would impact the health’ is too general, and ‘running would improve your health’ is too specific. Thus, the hypothesis for the above study is exercise does have an impact on the health of people.

Prediction of consequences

The hypothesis is the statement of the researcher’s assumption. Thus, it helps in predicting the ultimate outcome of the thesis.

Experience leads to better air traffic control management.

Even if the assumption of the researcher is proven false in testing, the result derived from the examination is valuable. With the presence of null and alternative hypotheses, each assessment of the hypothesis yields a valuable conclusion.

Separating irrelevant information from relevant information

 A hypothesis plays a significant role ineffectiveness of a study. It not only navigates the researcher but also prevents the researcher from building an inconclusive study. By guiding as light in the entire thesis, the hypothesis contributes to suggesting and testing the theories along with describing the legal or social phenomenon.

Navigate research

A hypothesis helps in identifying the areas that should be focused on for solving the research problem. It helps frame the concepts of study in a meaningful and effective manner. It also helps the researcher arrive at a conclusion for the study based on organized empirical data examination.

Prevents blind research

A hypothesis guides the researcher in the processes that need to be followed throughout the study. It prevents the researcher from collecting massive data and doing blind research which would prove irrelevant.

A platform for investigating activities

By examining conceptual and factual elements related to the problem of a thesis, the hypothesis provides a framework for drawing effective conclusions. It also helps stimulate further studies.

Describes a phenomenon

Each time a hypothesis is tested, more information about the concerned phenomenon is made available. Empirical support via hypothesis testing helps analyse aspects that were unexplored earlier.

Framing accurate research hypothesis statements

For the deduction of accurate and reliable outcomes from the analysis, belong stated things should be noted:

• Should never be formulated in the form of a question.
• Empirical testability of the hypothesis should be possible.
• A precise and specific statement of concept should be present.
• The hypothesis should not be contradictory to the identified concept and linkage between the variables.
• A clear specification of all the variables which are used for building relationships in the hypothesis should be present.
• The focus of a single hypothesis should only be on one issue. No multi-issue consideration should be taken while building the hypothesis i.e. could only be either relational or descriptive.
• The hypothesis should not be conflicting with the defined law of nature which is already specified as true.
• Effective tools and techniques need to be used for the verification of the hypothesis.
• The form of the hypothesis statement should be simple and understandable. Complex or conflicting statement reduces the applicability and reliability of the thesis results.
• The hypothesis should be amendable in the form that testing could be completed within a specified reasonable time.
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I am a management graduate with specialisation in Marketing and Finance. I have over 12 years' experience in research and analysis. This includes fundamental and applied research in the domains of management and social sciences. I am well versed with academic research principles. Over the years i have developed a mastery in different types of data analysis on different applications like SPSS, Amos, and NVIVO. My expertise lies in inferring the findings and creating actionable strategies based on them. 

Over the past decade I have also built a profile as a researcher on Project Guru's Knowledge Tank division. I have penned over 200 articles that have earned me 400+ citations so far. My Google Scholar profile can be accessed here . 

I now consult university faculty through Faculty Development Programs (FDPs) on the latest developments in the field of research. I also guide individual researchers on how they can commercialise their inventions or research findings. Other developments im actively involved in at Project Guru include strengthening the "Publish" division as a bridge between industry and academia by bringing together experienced research persons, learners, and practitioners to collaboratively work on a common goal. 

I am a Senior Analyst at Project Guru, a research and analytics firm based in Gurugram since 2012. I hold a master’s degree in economics from Amity University (2019). Over 4 years, I have worked on worked on various research projects using a range of research tools like SPSS, STATA, VOSViewer, Python, EVIEWS, and NVIVO. My core strength lies in data analysis related to Economics, Accounting, and Financial Management fields.

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A concise guide to reproducible research using secondary data

Chapter 2 formulating a hypothesis.

“There is no single best way to develop a research idea.” ( Pischke 2012 )

2.1 How do you develop a research question and formulate a hypothesis?

You decide to undertake a scientific project. Where do you start? First, you need to find a research question that interests you and formulate a hypothesis. We will introduce some key terminology, steps you can take, and examples how to develop research questions. Note that .

What if someone assigns a topic to me? For students attending undergraduate and graduate courses that often pick topics from a list, all of these steps are equally important and necessary. You still need to formulate a research question and a hypothesis. And it is important to clarify the relevance of your topic for yourself.

When thinking about a research question, you need to identify a topic that is:

• Relevant , important in the world and interesting to you as a researcher: Does working on the topic excites you? You will spend many hours thinking about it and working on it. Therefore, it should be interesting and engaging enough for you to motivate your continued work on this topic.
• Specific : not too broad and not too narrow
• Feasible to research within a given time frame: Is it possible to answer the research question based on your time budget, data and additional resources.

How do you find a topic or develop a feasible research idea in the first place? Finding an idea is not difficult, the critical part is to find a good idea. How do you do that? There is no one specific way how one gets an idea, rather there is a myriad of ways how people come up with potential ideas (for example, as stated by Varian ( 2016 ) ).

You can find inspiration by

• Looking at insights from the world around you: your own life and experiences, observe the behavior of people around you
• Talking to people around you, experts, other students, family members
• Talking to individuals outside your field (non-economists)
• Talking to professionals working in the area you are interested in (you may use social media and professional platforms like LinkedIN or Twitter to make contact)
• Reading journal articles from other non-economic social sciences and the medical literature
• What are the issues being discussed?
• How do these issues affect people’s lives?

In addition you could

• Go to virtual and in-person seminars, for example, the Essen Health Economics Seminar
• Look at abstracts of scientific articles and working papers
• Look at the literature in a specific field you are interested in, for example, screening complete issues of journals or editorials about certain research advancements. By reading this literature you might come up with the idea on how to extend and refine previous research.

Once you identified a research question that is of interest to you, you need to define a hypothesis.

2.2 What is a hypothesis?

A hypothesis is a statement that introduces your research question and suggests the results you might find. It is an educated guess. You start by posing an economic question and formulate a hypothesis about this question. Then you test it with your data and empirical analysis and either accept or reject the hypothesis. It constitutes the main basis of your scientific investigation and you should be careful when creating it.

2.2.1 Develop a hypothesis

Before you formulate your hypothesis, read up on the topic of interest. This should provide you with sufficient information to narrow down your research question. Once you find your question you need to develop a hypothesis, which contains a statement of your expectations regarding your research question’s results. You propose to prove your hypothesis with your research by testing the relationship between two variables of interest. Thus, a hypothesis should be testable with the data at hand. There are two types of hypotheses: alternative or null. Null states that there is no effect. Alternative states that there is an effect.

There is an alternative view on this that suggests one should not look at the literature too early on in the idea-generating process to not be influenced and shaped by someone else’s ideas ( Varian 2016 ) . According to this view you can spend some time (i.e. a few weeks) trying to develop your own original idea. Even if you end up with an idea that has already been pursued by someone else, this will still provide you with good practice in developing publishable ideas. After you have developed an idea and made sure that it was not yet investigated in the literature, you can start conducting a systematic literature review. By doing this, you can find some other interesting insights from the work of others that you can synthesize in your own work to produce something novel and original.

2.2.2 Identify relevant literature

For your research project you will need to identify and collect previous relevant literature. It should involve a thorough search of the keywords in relevant databases and journals. Place emphasis on articles from high-ranking journals with significant numbers of citations. This will give you an indication of the most influential and important work in the field. Once you identify and collect the relevant literature for your topic, you will need to critically synthesize it in your literature review.

When you perform your literature review, consider theories that may inform your research question. For example, when studying physician behavior you may consider principal-agent theory.

2.2.3 Research question or literature review: the chicken or the egg problem?

Whether you start reading the literature first or by developing an idea may depend on your level (graduate student, early career researcher) and other goals. However, thinking freely about what you like to investigate first may help to critically develop a feasible and interesting research question.

We highlight an example how to start with investigating the real world and subsequently posing a research question ( “How to Write a Strong Hypothesis Steps and Examples ” 2019 ; “Developing Strong Research Questions Criteria and Examples ” 2019 ; Schilbach 2019 ) . For example, based on your observation you notice that people spend extensive amount of time looking at their smartphones. Maybe even you yourself engage in the same behavior. In addition, you read a BBC News article Social media damages teenagers’ mental health, report says .

(#fig:social_media)Social media and mental health

Source: BBC

You decide to translate this article and your observations into a research question : How does social media use affect mental health? Before you formulate your hypothesis, read up on the topic of interest. Read economic, medical and other social science literature on the topic. There is likely to be a vast amount of literature from non-economic fields that are doing research on your topic of interest, for example, psychology or neuroscience. Familiarize yourself with it and master it. Do not get distracted by different scientific methodologies and techniques that might seem not up-to-par to the economic studies (small sample sizes, endogeneity, uncovering association rather than causation, etc.), but rather focus on suggestions of potential mechanisms.

A hypothesis is then your research question distilled into a one sentence statement, which presents your expectations regarding the results. You propose to prove your hypothesis by testing the relationship between two variables of interest with the data at hand. There are two types of hypotheses: alternative or null. The null hypothesis states that there is no effect. The alternative hypothesis states that there is an effect.

A hypothesis related to the above-stated research question could be: The increased use of social media among teenagers leads to (is associated with) worse mental health outcomes, i.e. increased incidence of depression, eating disorders, worse well-being and lower self-esteem. It suggests a direction of a relationship that you expect to find that is guided by your observations and existing evidence. It is testable with scientific research methods by using statistical analysis of the relevant data.

Your hypothesis suggests a relationship between two variables: social media use (your independent variable \(X\) ) and mental health (dependent variable \(Y\) ). It could be framed in terms of correlation (is associated with) or causation (leads to). This should be reflected in the choice of scientific investigation you decide to undertake.

The null hypothesis is: There is no relationship between social media use among teenagers and their mental health .

2.3 Resources box

2.3.1 how to develop strong research questions.

• The form of the research process
• Varian, H. R. (2016). How to build an economic model in your spare time. The American Economist, 61(1), 81-90.

2.3.2 Identify relevant literature from major general interest and field literature

To identify the relevant literature you can

• use academic search engines such as Google Scholar, Web of Science, EconLit, PubMed.
• search working paper series such as the National Bureau of Economic Research , NetEc or IZA
• search more general resource sites such as Resources for Economists
• go to the library/use library database

2.3.3 Assess the quality of a journal article

Several rankings may help to assess the quality of research you consider

• Journals of general interest and by field in economics and management - For German-speaking countries, consider the VWL / BWL Handelsblatt Ranking for economics and management - The German Association of Management Scholars provides an expert-based ranking VHB JourQual 3.0, Teilranking Management im Gesundheitswesen - Web of Science Impact Factors - Scimago
• Health Economics, Health Services and Health Care Managment Research: Health Economics Journals List
• Be aware that like in any other domain there are predatory publishing practices .

Use tools to investigate how a journal article is connected to other works

• Citationgecko
• Connected papers
• scite_ – a tool to get a first impression whether a study is disputed or academic consensus

2.3.4 Organize your literature

• Zotero (free of charge)
• Mendeley (free of charge)
• EndNote (potentially free of charge via your university)
• Citavi (potentially free of charge via your university)
• BibTEX if you work with TEX
• Excel spread sheet

2.4 Checklist to get started with formulating your hypothesis

• Find an interesting and relevant research topic, if not assigned
• Try to suck up all information you can easily obtain from various sources within and outside academic literature
• Formulate one compelling research question
• Find the best available empirical and theoretical evidence that is related to your research question
• Formulate a hypothesis
• Check whether data are available for analysis
• Challenge your idea with your fellows or senior researchers

2.5 Example: Hellerstein ( 1998 )

As an illustration of the research process of formulating a hypothesis, designing a study, running a study, collecting and analyzing the data and, finally, reporting the study, we provide an example by replicating Judith K. Hellerstein’s paper “The Importance of the Physician in the Generic versus Trade-Name Prescription Decision” that was published in 1998 in the RAND Journal of Economics.

Hellerstein’s 1998 paper has impacted discussion about behavioral factors of physician decisions and pharmaceutical markets over two decades. The study received 448 citations on Google Scholar since 1998 by 27/03/2022, including recent mentions in top field journals such as Journal of Public Economics (2021) , Journal of Health Economics (2019) , and Health Economics (2019) .

Figure 2.1: Connected graph of Hellerstein ( 1998 ) , February 2022

Figure 2.1 shows a connected graph of prior and derivative works related to the study.

The work has impacted the literature researching the role of physician behavior and its influence on access, adoption and diffusion of health services, moral hazard and incentives in prescription and treatment decisions and the influence of different payment schemes, and a vast body of literature studying the pharmaceutical market.

The research that has been influenced by Hellerstein includes evidence on:

• generic drug entries and market efficiency
• the effectiveness of pharmaceutical promotion
• the effectiveness of price regulations
• the role of patents and dynamics of market segmentation

At the end of each chapter, we demonstrate insights into this study that we replicate.

2.5.1 Context of the study - escalating health expenditures

In the United States, the total prescription drug expenditure in 2020 marked about 358.7 billion US Dollars ( Statista n.d. ) . The prescription of generic drugs in comparison to more expensive brand-name versions is an option in reducing the total health care expenditure. Generic drugs are bioequivalent in the active ingredients and can serve as a channel to contain prescription expenditure ( Kesselheim 2008 ) as generic drugs are between 20 and 90% cheaper than their trade-name alternatives ( Dunne et al. 2013 ) .

2.5.2 Research question - How does a patient’s insurance status influence the physician’s choice between generic compared to brand-name drugs?

Physicians are faced with a multitude of medication options, including the choice between generic and trade-name drugs. Physicians ideally act as agents for their patients to identify the best available treatment option based on their needs. Choosing the best treatment entails cost of coordination and cognition. The prescription of generic drugs may serve as an example to what extent physicians customize treatments according to patients’ needs with regards to cost. From an economic point of view we may expect that once a generic drug is available, a perfectly rational agent (i.e. physician) would prescribe a generic drug instead of the trade-name version if therapeutically identical ( Dranove 1989 ) . This leads to the following research question: “Do physicians vary their prescription decisions on a patient-by-patient basis or do they systematically prescribe the same version, trade-name or generic, to all patients?” .

The 1998 Hellerstein’s study examines two hypotheses:

• The physician prescribing choice influences the selection of a generic over a brand-name drug
• The patient’s insurance status influences the physician’s choice between generic and brand-name drugs.

For the purpose of this example and in the replication exercise we focus on the second aspect.

2.5.3 Hypothesis

The paper formulates the following hypothesis:

Physicians are more likely to prescribe generics to patients who do not have insurance coverage for prescription pharmaceuticals (moral hazard in insurance)

Hellerstein ( 1998 ) discusses that, based on insurance status, some patients may demand certain care more than others. If, for example, the prescription drug is reimbursed by the patient’s health insurance, this may cause overconsumption. This behavior can potentially differ by the patient’s insurance scheme. A patient that has no insurance and, thus, does not get any reimbursement for prescription drugs, might have a higher incentive to demand cheaper generic drugs ( Danzon and Furukawa 2011 ) than a patient with insurance that covers prescription drugs, either generic or trade-name. Given that the United States have different insurance schemes with varying prescription drug coverage, it is of interest to investigate the role of a patient’s insurance status in the physician’s choice between generic compared to brand-name drugs.

Hellerstein ( 1998 ) considers a patient’s insurance status as a matter of dividing the study population in groups for which the choice between generic and brand-name drugs differs. She suggests that There is a relationship between the prescription of a generic drug and insurance status of a patient. ( Hellerstein 1998 ) .

Providing answers to a research question requires formulating and testing a hypothesis. Based on logic, theory or previous research, a hypothesis proposes an expected relationship within the given data. According to her research question, Hellerstein hypothesizes that: Physicians are more likely to prescribe generics to patients who do not have insurance coverage for prescription pharmaceuticals.

Specifically, she writes “if there is moral hazard in insurance when it comes to physician prescription behavior, there will be differences in the propensity of physicians to prescribe low-cost generic drugs, and these differences will be (partially) a function of the insurance held by the patient. In particular, if moral hazard exists, patients with extensive insurance coverage for prescription drugs (like those on Medicaid in 1989) should receive prescriptions written for generic drugs less frequently than patients with no prescription drug coverage.” ( Hellerstein 1998, 113 )

Based on Hellerstein’s considerations, we expect the effect of the insurance status on whether a patient receives a generic to be different from zero. To obtain a testable null hypothesis, we reformulate this relationship so that we reject the hypothesis if our expectations are correct. This means, if we expect to see an effect of insurance on prescriptions of generics, our null hypothesis is that insurance status has no effect on the outcome (prescription of generic drugs). No moral hazard arises from having obtained insurance.

Public Health Notes

Your partner for better health, hypothesis in research: definition, types and importance .

April 21, 2020 Kusum Wagle Epidemiology 0

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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What is the Correct Way to Write a Hypothesis? Expert Tips and Examples

Crafting a solid hypothesis is a crucial step in the scientific research process. A well-formulated hypothesis not only guides your research but also provides a clear focus for your study. This article delves into expert tips and examples to help you write a strong hypothesis, ensuring your research is grounded in a solid theoretical framework.

Key Takeaways

• A hypothesis should be clear and precise, providing a specific prediction that can be tested.
• Preliminary research is essential to formulate a well-informed hypothesis based on existing literature and data.
• A strong hypothesis must be testable and falsifiable, meaning it can be proven or disproven through experimentation or observation.
• It is important to differentiate between null and alternative hypotheses, as both play crucial roles in scientific research.
• Avoid common pitfalls such as overly broad statements and ambiguous language to ensure your hypothesis is effective and meaningful.

Understanding the Fundamentals of a Hypothesis

A hypothesis is a foundational element in scientific research, serving as a preliminary answer to a research question. Understanding its fundamentals is crucial for any researcher. A well-crafted hypothesis not only guides the direction of your study but also provides a basis for statistical storytelling: understanding and applying key stats in experimental research .

Steps to Formulating a Strong Hypothesis

Identifying the research question.

The first step in formulating a strong hypothesis is to identify the main research question . This involves recognizing a pattern or phenomenon that piques your interest and then asking a specific question that your hypothesis will aim to answer. This step is crucial as it sets the direction for your targeted research .

Conducting Preliminary Research

Before you can formulate a hypothesis, you need to conduct preliminary research. This involves gathering as much information as possible about your topic. By reviewing existing literature and studies, you can gain insights into what is already known and identify gaps that your research could fill. This step ensures that your hypothesis is grounded in existing knowledge and is relevant to the field.

Formulating the Hypothesis Statement

Once you have identified your research question and conducted preliminary research, the next step is to formulate your hypothesis statement. A well-crafted hypothesis should be clear, specific, and testable. It should propose a relationship between variables that can be examined through experimentation or observation. Remember, a strong hypothesis not only predicts an outcome but also provides a basis for further investigation.

Characteristics of a Well-Written Hypothesis

A well-written hypothesis is essential for guiding your research and ensuring that your study is both meaningful and scientifically valid. Clarity and precision are paramount; your hypothesis should be articulated in a way that leaves no room for ambiguity. This means using specific language and clearly defining any terms or variables involved. A hypothesis must also be testable and falsifiable, meaning it should be structured in a way that allows for empirical testing and the possibility of being proven wrong. This is crucial for maintaining the scientific integrity of your research. Lastly, your hypothesis should be directly relevant to your research question, providing a focused direction for your study. By adhering to these characteristics, you can formulate a hypothesis that is both robust and reliable.

Types of Hypotheses in Research

Understanding the various types of hypotheses is crucial for any researcher. Each type serves a unique purpose and is used in different contexts to address the research question effectively.

Examples of Effective Hypotheses

Hypotheses in natural sciences.

In the natural sciences, hypotheses often predict relationships between variables based on empirical evidence. For instance, a hypothesis might state, "Plants exposed to higher levels of sunlight will grow faster than those in shaded areas." This hypothesis is clear and testable , making it a strong candidate for scientific investigation.

Hypotheses in Social Sciences

Social science hypotheses frequently address human behavior and societal trends. An example could be, "Individuals who engage in regular physical activity report higher levels of happiness compared to those who do not." This hypothesis is relevant to the research question and can be tested through surveys and observational studies.

Hypotheses in Applied Research

Applied research often focuses on practical problems and solutions. A typical hypothesis might be, "Implementing a four-day workweek will increase employee productivity." This hypothesis is specific and actionable , providing a clear direction for research and potential policy changes.

Common Pitfalls and How to Avoid Them

When crafting a hypothesis, it's crucial to be aware of common pitfalls that can undermine your research. Avoiding these mistakes will enhance the quality and reliability of your study.

Expert Tips for Writing a Hypothesis

Consulting existing literature.

Before you start formulating your hypothesis, it's crucial to delve into existing literature. This step helps in demystifying the concept of a thesis statement and provides a foundation for your research. By reviewing previous studies, you can identify gaps in the research and build upon them. This not only strengthens your hypothesis but also ensures its relevance in the academic community.

Peer Review and Feedback

Engaging with peers and mentors for feedback is an invaluable part of the hypothesis-writing process. Constructive criticism can help you refine your hypothesis, making it more precise and testable. Don't hesitate to share your drafts and be open to suggestions. This collaborative approach can significantly reduce thesis anxiety and improve the quality of your work.

Iterative Refinement

Writing a hypothesis is not a one-time task; it requires iterative refinement. Start with a broad idea and gradually narrow it down through multiple revisions. This process involves continuously testing and tweaking your hypothesis to ensure it aligns with your research objectives. Remember, a well-crafted hypothesis is the result of meticulous planning and constant improvement.

Crafting a solid hypothesis is crucial for the success of your thesis. Our experts at Research Rebels have compiled essential tips to guide you through this process. Don't let uncertainty hold you back. Visit our website to explore our comprehensive Thesis Action Plan and claim your special offer now !

In conclusion, writing a hypothesis is a fundamental step in the scientific research process that requires careful consideration and precision. By following the expert tips and examples provided in this article, researchers can craft hypotheses that are clear, testable, and relevant to their studies. A well-formulated hypothesis not only guides the direction of the research but also provides a framework for analyzing results and drawing meaningful conclusions. As such, mastering the art of hypothesis writing is essential for any researcher aiming to contribute valuable insights to their field of study.

Frequently Asked Questions

What is a hypothesis.

A hypothesis is a tentative statement predicting a relationship between variables, which can be tested through scientific research.

Why is a hypothesis important in scientific research?

A hypothesis provides a focused direction for research, allowing scientists to make predictions and test their validity through experimentation.

What are the key characteristics of a well-written hypothesis?

A well-written hypothesis should be clear, precise, testable, falsifiable, and relevant to the research question.

What is the difference between a null hypothesis and an alternative hypothesis?

A null hypothesis states that there is no effect or relationship between variables, while an alternative hypothesis suggests that there is an effect or relationship.

How can I ensure my hypothesis is testable?

To ensure your hypothesis is testable, it should be specific and measurable, with clearly defined variables and a methodology for testing.

What are common mistakes to avoid when writing a hypothesis?

Common mistakes include making hypotheses that are too broad, using ambiguous language, and failing to ensure the hypothesis is testable.

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• Formulation of Hypothesis

Children who spend more time playing outside are more likely to be imaginative. What do you think this statement is an example of in terms of scientific research ? If you guessed a hypothesis, then you'd be correct. The formulation of hypotheses is a fundamental step in psychology research.

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What is a hypothesis? 

What method states that a hypothesis needs to be formulated to produce good research?

What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV, and states how it will influence the DV. 

Which type of hypothesis is also known as a two-tailed hypothesis? 

What are the requirements of a good hypothesis? 

What steps do researchers need to take when formulating a testable hypothesis? 

What is a hypothesis predicting? 

What type of hypothesis matches the following definition. A predictive statement that researchers use when it is thought that the IV will not influence the DV.

What type of hypothesis is the following example. There will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

Why are hypotheses needed in research? 

What is an operationalised variable?

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• First, we will discuss the importance of hypotheses in research.
• We will then cover formulating hypotheses in research, including the steps in the formulation of hypotheses in research methodology.
• We will provide examples of hypotheses in research throughout the explanation.
• Finally, we will delve into the different types of hypotheses in research.

What is a Hypothesis?

The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . To be classed as scientific research , it must be observable, valid, reliable and follow a standardised procedure.

One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.

The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.

The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.

In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.

If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.

Importance of Hypothesis in Research

The purpose of including hypotheses in psychology research is:

• To provide a summary of the research, how it will be investigated, and what is expected to be found.
• To provide an answer to the research question.

When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.

Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.

The researcher then forms a research question that the researcher will attempt to answer in their study.

Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.

The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology

Researchers must follow certain steps to formulate testable hypotheses when conducting research.

Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables ? Or will it be more concerned with the correlation between variables?

All researchers will likely complete the following.

• Investigating background research in the area of interest.
• Formulating or investigating a theory.
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.

The above steps are used to formulate testable hypotheses.

The Formulation of Testable Hypotheses

The hypothesis is important in research as it indicates what and how a variable will be investigated.

The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.

This is known as the scientific method.

Formulating Hypotheses in Research

When formulating hypotheses, things that researchers should consider are:

Types of Hypotheses in Research

Researchers can propose different types of hypotheses when carrying out research.

The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression ."

The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.

The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.

In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.

An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.

The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.

The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.

The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.

Example Hypothesis in Research

To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables: the independent and the dependent.

If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.

Formulation of Hypothesis - Key Takeaways

• The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. One of the important steps in scientific research is to create a hypothesis.
• The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
• Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
• There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
• There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).

Flashcards in Formulation of Hypothesis 18

The hypothesis is a predictive, testable statement concerning the outcome/ results the researcher expects to find. 

The scientific method states that researchers need to formulate a good hypothesis before starting the research. 

Directional, alternative hypothesis 

Alternative hypothesis 

A good hypothesis should:

• identify and operationalise the independent and dependent variable
• be testable 
• be falsifiable 
• predictive statements 

All researchers will likely complete the following

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

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Frequently Asked Questions about Formulation of Hypothesis

What are the 3 types of hypotheses?

The three types of hypotheses are:

• Null hypothesis 
• Alternative hypothesis 
• Directional/non-directional hypothesis 

What is an example of a hypothesis in psychology?

An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

What are the steps in formulating a hypothesis?

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

What is formulation of hypothesis in research? 

The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.

How to formulate  null and alternative hypothesis?

When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go. 

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Why is formulating a hypothesis important?

putting a certain hypothesis is important for the person making a certain experiment.For exampe,if s/he were a scientist,the hypothesis would help in knowing what experiments should be done(in another words,NO hypothesis-->NO experiments will be done).

Add your answer:

Procedure for formulating accounting standards in India?

kindly show the process of formulating accounting stardards

What is the outcome of hypothesis testing?

a. the hypothesis ispartly true but needs to be revised. b. the hypothesis wrong. c. the hypothesis is supported. d. the hypothesis is of no value.

What is deductive method in economics?

The deductive method is a very important method for testing theories or hypotheses. It is sometimes said to be "the scientific method". Its application can be divided into four stages :Identify the hypothesis to be tested.Generate predications from the hypothesis.Use experiments to check whether predictions are correct.If the predictions are correct, then the hypothesis is confirmed. If not, then the hypothesis is disconfirmed.The Deductive Research Method works from the more general to the more specific. [Theory > Hypothesis > Observation > Confirmation]

Two reason why an experiment might not support a hypothesis even when the hypothesis is correct?

An experiment might not support a hypothesis even if the hypothesis is correct because if the conclusion

Who of the following is responsible for formulating educational policy?

a state government

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solved Formulate and evaluate hypothesis tests for population parameters based on

Formulate and evaluate hypothesis tests for population parameters based on sample statistics using both Critical Regions and P-Values, and be able to state results in a non-technical way that can be understood by consumers of the data instead of statisticians. Dealing with Two Populations: Inferential statistics involves forming conclusions about a population parameter. We do so by constructing confidence intervals and testing claims about a population mean and other statistics. Typically, these methods deal with a sample from one population. We can extend the methods to situations involving two populations (and there are many such applications). This deliverable looks at two scenarios. Concept being Studied: Your focus is on hypothesis tests and confidence intervals for two populations using two samples, some of which are independent and some of which are dependent. These concepts are an extension of hypothesis testing and confidence intervals which use statistics from one sample to make conclusions about population parameters.

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What to Know About the Updated COVID Vaccine for Fall, Winter 2024–25

The updated COVID vaccine provides safe, effective protection against current variants for everyone 6 months and older.

Aliza Rosen

Amid an unexpectedly large surge of summer COVID infections in the U.S., and with the fall/winter virus season around the corner, updated COVID vaccines have arrived.

COVID vaccines are one of the best and safest ways to protect against severe illness and hospitalization. Updated COVID vaccines are chosen to target the variants currently circulating and are recommended for everyone 6 months of age and older.

In this Q&A, Andy Pekosz , PhD, a professor in Molecular Microbiology and Immunology , discusses who the updated vaccine is recommended for, when to get yours, whether it’s safe to get it alongside other seasonal vaccines.

What’s new about this year’s updated COVID vaccines?

The updated mRNA COVID vaccines from Moderna and Pfizer are based on the KP.2 strain, one of the FLiRT variants that have been spreading since early spring. These variants and their sub-variants have caused the majority of infections during this summer’s COVID wave.

Who should be getting an updated COVID vaccine?

Everyone 6 months and older should get vaccinated against COVID, according to the CDC’s recommendations .

For children ages 6 months to 4 years: Vaccination is recommended, but the number of vaccinations is based on which vaccine they receive, their age, and whether they’ve received a previous COVID vaccine. Parents and guardians should refer to CDC guidance and check with their pediatrician to see what’s recommended for their child.

For people ages 5 years and up: One dose of the updated COVID vaccine is recommended, regardless of whether they’ve been vaccinated previously. If someone has received a COVID vaccine recently, they should wait at least two months before getting the updated one for this season.

According to updated CDC guidelines, individuals who are immunocompromised may receive additional doses with their health care provider’s guidance.

When is the best time to get vaccinated?

This summer’s surge has been larger and lasted longer than many experts anticipated, making it a little trickier than years past to determine the best time to get vaccinated.

People who have not had COVID in the past few months have a couple options:

• Get the updated COVID vaccine as soon as it’s available  (late August, early September) to protect yourself as the wave of summer infections continues.
• Get the updated COVID vaccine around mid-October to build protection in time for the rise of cases that typically occur around November through January.

People at higher risk of severe illness should consider getting an updated COVID vaccine as soon as possible. Everyone who is eligible should get an updated COVID vaccine by mid-October in order to build immunity ahead of holiday travel and gatherings. Remember, it takes about two weeks to build up immunity following a vaccine, so schedule your vaccination accordingly.

How long does protection last after I'm vaccinated?

Broadly speaking, the COVID vaccine provides strong protection against infection for up to three months and protection against severe disease out to six months. That said, there are a lot of variables that can affect duration and strength of protection, including any new variants that may emerge and how different they are from the vaccine formulation.

If I had COVID recently, when should I get the updated vaccine?

If you’ve had COVID this summer, you’ll have strong infection-based immunity and can wait a few months after your infection before getting the vaccine. According to the CDC, you can wait three months since your symptoms began or, for asymptomatic cases, since you first tested positive.

There’s some evidence to support waiting as long as six months after a COVID infection to receive an updated vaccine. Waiting longer than the CDC’s guidance of three months is not recommended for high-risk groups, but it’s something people can discuss with their doctor.

How should I choose which COVID vaccine to get?

Between the two mRNA vaccines from Moderna and Pfizer, there is no reason to get one over the other. They target the same KP.2 variant, are similarly effective, and elicit similar side effects.

Is the COVID vaccine free?

The COVID vaccine is free under most health insurance plans and Medicare.

If you don’t have insurance to cover the cost of the COVID vaccine, look for vaccination clinics run by your local or state health department. Children under 18 may also be eligible to get a free COVID vaccine through the CDC’s Vaccines for Children Program .

You can find local pharmacies offering COVID vaccines at Vaccines.gov or by contacting your health care provider or local health department.

Are there any side effects to the updated COVID vaccine?

The common side effects are the same as with previous COVID vaccines. Symptoms like soreness at the injection site, achiness or joint pain, fatigue, slight fever, chills, or nausea are normal and not cause for concern. These side effects are a sign that your body is mounting an immune response—exactly what it’s supposed to do following a vaccine. Side effects generally subside within a day or two.

If I haven’t gotten any COVID vaccines yet, can I start with this one?

If you’ve never been vaccinated against COVID, now is a great time to start. People 5 years of age and older are considered up to date on COVID vaccination once they receive one dose of an updated mRNA COVID vaccine.

How well does the vaccine protect against the variants currently circulating?

The vaccine is a close match to variants currently circulating and provides good protection against severe disease, hospitalization, and death. While KP.2 is not causing a significant number of infections, the most prevalent variants circulating right now are very closely related to them. The vaccine will never be a perfect match to the circulating variants because it takes 2-4 months to make the vaccine, and during that time the virus continues to change as it infects people.

Is vaccine-induced immunity better than immunity from infection?

Vaccine-induced immunity is better because it’s safer. When you get infected with COVID, symptoms from the infection wreak havoc on your body. Whether or not you’ve been infected or vaccinated previously, the updated COVID vaccine is going to strengthen your immune responses to high levels and do so in a safe way.

Can I still get COVID if I’m vaccinated?

People who are vaccinated can still get COVID, but it is much more likely they will experience mild symptoms. Vaccinated people are much less likely to experience severe illness or get so sick that they need to be hospitalized. Data continue to show that those who are hospitalized with COVID are largely people who have not received a COVID vaccine within the past 12 months.

Particularly for people at higher risk of severe COVID, vaccination is an essential tool for reducing COVID complications, hospitalization, and death.

Can you get the flu shot and the COVID vaccine at the same time?

Yes! In fact, studies have shown that people who decide to spread out their vaccines into separate appointments often don’t follow through with getting both. We’ve also seen that the immune response generated by each vaccine does not change based on whether they are administered at the same time or separately.

It’s important to remember that many of the same populations at high risk of experiencing severe illness from COVID are also at high risk of severe influenza. Especially for these vulnerable populations, it’s a good idea to time your vaccines together.

When might we see a combined COVID and flu vaccine?

Some vaccine manufacturers have been working on developing a combined vaccine for COVID and flu, but we’re not there yet. We certainly won’t see a combined vaccine this year. It’s possible one will be ready in time for fall 2025, but we won’t know for sure until more clinical trial results are available.  

Aliza Rosen is a digital content strategist in the Office of External Affairs at the Johns Hopkins Bloomberg School of Public Health.

Related Articles:

• Understanding the CDC’s Updated COVID Isolation Guidance
• What to Know About COVID FLiRT Variants
• The Long History of mRNA Vaccines

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Effectiveness of the 2023–2024 Formulation of the COVID-19 Messenger RNA Vaccine

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Nabin K Shrestha, Patrick C Burke, Amy S Nowacki, Steven M Gordon, Effectiveness of the 2023–2024 Formulation of the COVID-19 Messenger RNA Vaccine, Clinical Infectious Diseases , Volume 79, Issue 2, 15 August 2024, Pages 405–411, https://doi.org/10.1093/cid/ciae132

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The purpose of this study was to evaluate whether the 2023–2024 formulation of the coronavirus disease 2019 (COVID-19) messenger RNA vaccine protects against COVID-19.

Cleveland Clinic employees when the 2023–2024 formulation of the COVID-19 messenger RNA vaccine became available to employees were included. Cumulative incidence of COVID-19 over the following 17 weeks was examined prospectively. Protection provided by vaccination (analyzed as a time-dependent covariate) was evaluated using Cox proportional hazards regression, with time-dependent coefficients used to separate effects before and after the JN.1 lineage became dominant. The analysis was adjusted for the propensity to get tested, age, sex, pandemic phase when the last prior COVID-19 episode occurred, and the number of prior vaccine doses.

Among 48 210 employees, COVID-19 occurred in 2462 (5.1%) during the 17 weeks of observation. In multivariable analysis, the 2023–2024 formula vaccinated state was associated with a significantly lower risk of COVID-19 before the JN.1 lineage became dominant (hazard ratio = .58; 95% confidence interval [CI] = .49–.68; P < .001), and lower risk but one that did not reach statistical significance after (hazard ratio = .81; 95% CI = .65–1.01; P = .06). Estimated vaccine effectiveness was 42% (95% CI = 32–51) before the JN.1 lineage became dominant, and 19% (95% CI = −1–35) after. Risk of COVID-19 was lower among those previously infected with an XBB or more recent lineage and increased with the number of vaccine doses previously received.

The 2023–2024 formula COVID-19 vaccine given to working-aged adults afforded modest protection overall against COVID-19 before the JN.1 lineage became dominant, and less protection after.

• vaccination
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NASA Extends Boeing Starliner Astronauts’ Space Station Stay to 2025

Persistent concerns with the vehicle’s propulsion systems mean Suni Williams and Butch Wilmore will return home next year in a SpaceX vehicle.

Boeing Starliner Astronauts Will Return to Earth in SpaceX Vehicle

Nasa announced that two astronauts aboard the international space station will have their stay extended by several months and that they will return on a spacex capsule because of problems with the boeing starliner..

“NASA has decided that Butch and Suni will return with Crew 9 next February and that Starliner will return uncrewed. A test flight by nature is neither safe nor routine. And so the decision to keep Butch and Suni aboard the International Space Station and bring the Boeing Starliner home uncrewed is the result of a commitment to safety.” “I talked with Butch and Suni both yesterday and today. They support the agency’s decision fully, and they’re ready to continue this mission on board I.S.S. as members of the Expedition 71 crew. Their families are doing well. Their families understand, just like the crew members when they launch, there’s always an opportunity, there’s always a possibility that they could be up there much longer than they anticipate. So the families understand that. I’m not saying it’s not hard. It is hard. It’s difficult.”

By Kenneth Chang

Two astronauts who have spent months aboard the International Space Station will have to stay there months longer after NASA decided on Saturday that they could not return on Boeing’s troubled Starliner space vehicle. They will return instead on a SpaceX capsule next year.

That decision finally brings clarity to the saga of the two NASA astronauts, Suni Williams and Butch Wilmore, who docked at the space station as part of a test flight of the Boeing vehicle. It also adds to months of difficult problems experienced by Boeing, a dominant aerospace company that has faced embarrassing setbacks in its much larger civilian aviation and defense divisions this year.

“A test flight by nature is neither safe nor routine,” Bill Nelson, the NASA administrator, said during a news conference, “and so the decision to keep Butch and Suni aboard the International Space Station and bring the Boeing Starliner home uncrewed is a result of a commitment to safety.”

Norman Knight, NASA’s flight operations director, said he had talked to Ms. Williams and Mr. Wilmore, and that they backed the extended stay in orbit, which officials have resisted describing as a stranding .

“They support the agency’s decision fully, and they’re ready to continue this mission onboard I.S.S.,” Mr. Knight said.

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