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The Craft of Writing a Strong Hypothesis

Table of Contents

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

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

What is a Hypothesis?

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

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

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

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

Different Types of Hypotheses‌

Types of hypotheses

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

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

1. Null hypothesis

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

2. Alternative hypothesis

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

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

3. Simple hypothesis

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

4. Complex hypothesis

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

5. Associative and casual hypothesis

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

6. Empirical hypothesis

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

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

7. Statistical hypothesis

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

Characteristics of a Good Hypothesis

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

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

Separating a Hypothesis from a Prediction

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

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

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

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

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

Finally, How to Write a Hypothesis

Quick tips on writing a hypothesis

1.  Be clear about your research question

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

2. Carry out a recce

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

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

3. Create a 3-dimensional hypothesis

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

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

4. Write the first draft

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

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

5. Proof your hypothesis

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

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

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

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

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

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

Frequently Asked Questions (FAQs)

1. what is the definition of hypothesis.

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

2. What is an example of hypothesis?

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

3. What is an example of null hypothesis?

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

4. What are the types of research?

• Fundamental research

• Applied research

• Qualitative research

• Quantitative research

• Mixed research

• Exploratory research

• Longitudinal research

• Cross-sectional research

• Field research

• Laboratory research

• Fixed research

• Flexible research

• Action research

• Policy research

• Classification research

• Comparative research

• Causal research

• Inductive research

• Deductive research

5. How to write a hypothesis?

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

• Avoid wordiness by keeping it simple and brief.

• Your hypothesis should contain observable and testable outcomes.

• Your hypothesis should be relevant to the research question.

6. What are the 2 types of hypothesis?

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

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

7. Difference between research question and research hypothesis?

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

8. What is plural for hypothesis?

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

9. What is the red queen hypothesis?

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

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

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

11. When to reject null hypothesis?

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

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Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

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

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

Some key points about hypotheses:

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

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

Types of Research Hypotheses

Alternative hypothesis.

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

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

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

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

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

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

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

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

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

Null Hypothesis

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

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

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

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

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

Nondirectional Hypothesis

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

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

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

Directional Hypothesis

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

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

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

Falsifiability

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

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

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

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

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

Can a Hypothesis be Proven?

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

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

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

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

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

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

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

How to Write a Hypothesis

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

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

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

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

More Examples

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

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Educational resources and simple solutions for your research journey

What is a Research Hypothesis: How to Write it, Types, and Examples

Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.  

It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .  

Table of Contents

What is a hypothesis ?  

A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.  

What is a research hypothesis ?  

Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”   

A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.     

Characteristics of a good hypothesis  

Here are the characteristics of a good hypothesis :  

• Clearly formulated and free of language errors and ambiguity  
• Concise and not unnecessarily verbose  
• Has clearly defined variables  
• Testable and stated in a way that allows for it to be disproven  
• Can be tested using a research design that is feasible, ethical, and practical   
• Specific and relevant to the research problem  
• Rooted in a thorough literature search  
• Can generate new knowledge or understanding.  

How to create an effective research hypothesis  

A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.  

Let’s look at each step for creating an effective, testable, and good research hypothesis :  

• Identify a research problem or question: Start by identifying a specific research problem.   
• Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.   
• Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.  
• State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.   
• Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.  
• Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .  

Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.  

How to write a research hypothesis  

When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.  

An example of a research hypothesis in this format is as follows:  

“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”  

Population: athletes  

Independent variable: daily cold water showers  

Dependent variable: endurance  

You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.  

Research hypothesis checklist  

Following from above, here is a 10-point checklist for a good research hypothesis :  

• Testable: A research hypothesis should be able to be tested via experimentation or observation.  
• Specific: A research hypothesis should clearly state the relationship between the variables being studied.  
• Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.  
• Falsifiable: A research hypothesis should be able to be disproven through testing.  
• Clear and concise: A research hypothesis should be stated in a clear and concise manner.  
• Logical: A research hypothesis should be logical and consistent with current understanding of the subject.  
• Relevant: A research hypothesis should be relevant to the research question and objectives.  
• Feasible: A research hypothesis should be feasible to test within the scope of the study.  
• Reflects the population: A research hypothesis should consider the population or sample being studied.  
• Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.  

By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.  

Types of research hypothesis  

Different types of research hypothesis are used in scientific research:  

1. Null hypothesis:

A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.   

Example: “ The newly identified virus is not zoonotic .”  

2. Alternative hypothesis:

This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.  

Example: “ The newly identified virus is zoonotic .”  

3. Directional hypothesis :

This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.   

Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”   

4. Non-directional hypothesis:

While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.  

Example, “ Cats and dogs differ in the amount of affection they express .”  

5. Simple hypothesis :

A simple hypothesis only predicts the relationship between one independent and another independent variable.  

Example: “ Applying sunscreen every day slows skin aging .”  

6 . Complex hypothesis :

A complex hypothesis states the relationship or difference between two or more independent and dependent variables.   

Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)  

7. Associative hypothesis:  

An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.  

Example: “ There is a positive association between physical activity levels and overall health .”  

8 . Causal hypothesis:

A causal hypothesis proposes a cause-and-effect interaction between variables.  

Example: “ Long-term alcohol use causes liver damage .”  

Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.  

Research hypothesis examples  

Here are some good research hypothesis examples :  

“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”  

“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”  

“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”  

“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”  

Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.   

Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:  

“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)  

“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)  

“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)  

Importance of testable hypothesis  

If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.  

To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.  

Frequently Asked Questions (FAQs) on research hypothesis  

1. What is the difference between research question and research hypothesis ?  

A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.

2. When to reject null hypothesis ?

A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.  

3. How can I be sure my hypothesis is testable?  

A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:  

• Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.  
• The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.   
• You should be able to collect the necessary data within the constraints of your study.  
• It should be possible for other researchers to replicate your study, using the same methods and variables.   
• Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.  
• The hypothesis should be able to be disproven or rejected through the collection of data.  

4. How do I revise my research hypothesis if my data does not support it?  

If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.  

5. I am performing exploratory research. Do I need to formulate a research hypothesis?  

As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.  

6. How is a research hypothesis different from a research question?

A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.

7. Can a research hypothesis change during the research process?

Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.

8. How many hypotheses should be included in a research study?

The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.

9. Can research hypotheses be used in qualitative research?

Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.

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The 3 Required Parts of a Hypothesis: Understanding the Basics

• by Brian Thomas
• October 9, 2023

Have you ever wondered what it takes to create a hypothesis? Whether you’re a student delving into scientific research or just curious about the world around you, understanding the key components of a hypothesis is essential. In this blog post, we’ll explore the three required parts of a hypothesis, breaking down their importance and providing real-world examples along the way.

A hypothesis serves as the foundation of any scientific investigation , allowing researchers to form predictions and test their ideas. But what are these three essential elements that make up a hypothesis? How do you develop a hypothesis that is effective and meaningful? Join us as we unravel the mysteries of hypothesis writing and explore the stages of hypothesis testing. By the end of this post, you’ll be equipped with the knowledge to craft your own hypotheses and embark on exciting scientific endeavors. So let’s dive in!

What Are the 3 Essential Components of a Hypothesis?

When it comes to hypotheses, the three key components are like the three musketeers of scientific inquiry. Each element plays an important role in shaping the hypothesis and guiding the research process. So, let’s dive into the three essential parts of a hypothesis and unravel their roles, shall we?

The Sneaky Subject: “If”

The first amigo of our hypothesis trio is the sneaky subject “If.” This little word sets the stage for your hypothesis, introducing the condition or factor you are exploring in your research. It’s like the Sherlock Holmes of hypotheses, searching for clues and connections. Without the “If,” our hypothesis would be as lost as a penguin in the Sahara.

The Clever Connection: “Then”

Ah, the clever companion “Then” joins the hypothesis party! This element helps you establish the expected outcome based on your “If” condition. It’s the bridge that connects your hypothesis to the results you hope to find. Think of it as the conductor of a symphony, orchestrating the relationship between the “If” and the “Then” in harmonious scientific fashion.

The Mighty Explanation: “Because”

Last but certainly not least, we have the mighty explanation “Because.” This component adds depth and substance to your hypothesis by providing a rationale or reason for your expected outcome. It’s like the wise old sage who imparts wisdom and knowledge. With the “Because” in place, your hypothesis transforms from a mere statement into a well-grounded prediction.

Putting It All Together

Now that we’ve met the three essential parts of a hypothesis, let’s see how they work together in a hypothetical example:

If eating chocolate leads to increased happiness, then individuals who consume chocolate daily because they have lower stress levels will report higher levels of satisfaction and well-being.

In this example, the “If” identifies the condition being explored (eating chocolate), the “Then” predicts the expected outcome (higher levels of satisfaction and well-being), and the “Because” provides the rationale (lower stress levels). It’s like a mini science equation, where each element contributes to the overall hypothesis.

Hypotheses are like the backbone of scientific research, guiding the direction and purpose of investigations. By understanding the three essential components – the sneaky “If,” clever “Then,” and mighty “Because” – you’re equipped to construct robust hypotheses that withstand the scrutiny of the scientific world. So, go forth and let your hypotheses shine like beacons of knowledge in the vast sea of research!

Remember, the next time you encounter a hypothesis, you’ll know its secret formula: “If” + “Then” + “Because” = scientific awesomeness!

FAQ: What are the 3 Required Parts of a Hypothesis?

Welcome to our comprehensive FAQ-style guide on hypotheses! If you’ve ever wondered about the key components of a hypothesis or how to develop one for your research paper, you’ve come to the right place. In this FAQ, we’ll address common questions and provide you with the information you need in a friendly, engaging, and even humorous way. So, grab a cup of coffee and let’s dive in!

What are the Requirements for a Hypothesis

A hypothesis is an essential part of the scientific method, serving as a description of the expected outcome of a research study. It must meet a few requirements to be considered valid:

Clear and Testable : A hypothesis should be formulated in a way that allows it to be empirically tested or proved wrong. Fuzzy or ambiguous hypotheses won’t hold up under scrutiny, so precision is key.

Based on Existing Knowledge : Your hypothesis should be grounded in previous research or observations. It should build upon what is already known in the field, helping to advance scientific understanding.

Specific and Measurable : A good hypothesis needs to be specific and measurable, allowing for objective evaluation. Vague statements won’t cut it – scientists want something concrete to sink their teeth into.

What Makes a Valid Hypothesis? 3 Things!

A valid hypothesis possesses three crucial characteristics, which we’ll explore in detail:

Dependent and Independent Variables : To create a valid hypothesis, you need to identify the dependent and independent variables. The dependent variable is the outcome you’re investigating, while the independent variable is the one manipulated to measure its effect on the dependent variable. This relationship forms the core of your hypothesis.

Directional Statement : Your hypothesis should include a directional statement that predicts the expected outcome of your research. Will the independent variable have a positive, negative, or no effect on the dependent variable? Don’t be shy – make a bold prediction!

Testability : A hypothesis must be testable through experiments or observations. This means you need to design a method to gather data and analyze whether it supports or refutes your hypothesis. It’s all about putting your hypothesis to the test and embracing scientific scrutiny.

What is a Hypothesis Example

Let’s put theory into practice with an example: – Hypothesis: “Increasing the amount of sunlight exposure will lead to faster plant growth.” – In this example, the dependent variable is plant growth, while the independent variable is the amount of sunlight exposure. The hypothesis is clear, testable, and includes a directional statement. Now go out there and test it with your green thumbs!

What are the Main Characteristics of a Hypothesis

A good hypothesis possesses several key characteristics. Take a look at these essential traits:

Precise : A hypothesis should be clear and unambiguous to avoid misinterpretation or confusion. Leave no room for doubt!

Falsifiable : For a hypothesis to be valid, it must be capable of being disproven or proven wrong. It should be open to testing and potential refutation.

Relevant : It’s important for a hypothesis to be relevant to the research question or problem at hand. It should address a specific aspect and contribute to the existing body of knowledge.

Logical : Logical coherence is crucial in a hypothesis. There should be a clear connection between the proposed relationship of variables and any supporting evidence or rationale.

What’s a Research Hypothesis

A research hypothesis is a statement formulated to predict a possible outcome of a research study. It serves as a proposed explanation or prediction based on existing knowledge and sets the groundwork for further investigation. Research hypotheses help guide scientific research and provide a clear focus for researchers to explore.

How Do You Write a Hypothesis for a Research Paper

When writing a hypothesis for a research paper, remember these steps:

Identify the Variables : Determine the dependent and independent variables in your study. The dependent variable is the outcome you’re interested in, while the independent variable is the one you’re manipulating.

Formulate a Question : Based on your research and variables, frame a clear and specific research question that links the variables together.

Craft a Statement : Turn your research question into a statement that predicts the relationship between the variables. Make it precise, testable, and include a directional statement.

Revise and Refine : Review your hypothesis for clarity, testability, and logical coherence. Refine it until it accurately represents your research expectations.

Research papers thrive on solid hypotheses, so take the time to craft yours with care!

What are Three Types of Scientific Studies

Scientific studies come in different flavors, each serving a unique purpose:

Observational Studies : These studies involve observing and analyzing existing data or phenomena without manipulating variables. They help identify associations or relationships but can’t establish causation.

Experimental Studies : Experimental studies involve manipulating variables to observe their effects on the dependent variable. These studies allow for causal relationships to be established.

Descriptive Studies : Descriptive studies seek to describe characteristics or behaviors within a population. They often involve surveys, interviews, or observations to collect data.

Consider the nature of your research to determine which type of study is most appropriate for your hypothesis.

How Do You Develop a Research Hypothesis

Developing a research hypothesis requires careful consideration and planning. Follow these steps:

Review Existing Literature : Familiarize yourself with the relevant research already conducted in your field. What questions remain unanswered? What potential gaps can you address?

Identify Variables : Determine the key variables involved in your study. Specify the independent and dependent variables that establish the relationship to be tested.

Formulate a Hypothesis : Create a clear and testable hypothesis that predicts the expected outcome. Make sure it aligns with previous research, is specific, and includes a directional statement.

Refine and Iterate : Continuously refine and iterate your hypothesis as you gather more information and insights. Adapt it based on feedback, new findings, or emerging theories.

Developing a research hypothesis is an iterative process that requires thoughtfulness and adaptability. Embrace the journey!

What are the Needs of Hypothesis in Research

Hypotheses play a vital role in the research process. Here are the key needs they fulfill:

Focus : Hypotheses provide a clear focus for research efforts by highlighting the expected outcome and guiding the investigation.

Testability : Hypotheses allow researchers to design experiments and collect data to test their predictions. This allows for objective evaluation and validation.

Advancement of Knowledge : By formulating hypotheses, researchers contribute to the existing body of knowledge in their field. They add new insights and build upon previous work.

Logic and Coherence : Hypotheses drive research by providing a logical framework and rationale for conducting the study. They ensure that research efforts are purposeful and well-grounded.

What are Types of Hypothesis

Hypotheses can fall into different categories based on their nature and purpose. Here are a few common types:

Null Hypothesis : The null hypothesis states that there is no significant relationship between the variables under investigation. Researchers aim to reject this hypothesis to support their alternative hypothesis.

Alternative Hypothesis : The alternative hypothesis reflects the researcher’s prediction of a specific relationship between variables. It’s the opposite of the null hypothesis and what researchers hope to support.

Directional Hypothesis : A directional hypothesis predicts the direction of the relationship between variables. It specifies whether the effect will be positive or negative, leaving no room for ambiguity.

Non-Directional Hypothesis : In contrast, a non-directional hypothesis simply predicts that a relationship exists between variables, without specifying the direction.

Consider the specific context of your research to determine the most appropriate type of hypothesis to formulate.

What are the Stages of Hypothesis

The hypothesis goes through several stages in the research process:

Formulation : In this initial stage, the researcher identifies the research question, variables, and constructs a hypothesis to guide the investigation.

Design : The hypothesis helps determine the research design and methodology. It guides the selection of variables, sample size, data collection methods, and statistical analyses.

Testing : During this stage, the researcher collects and analyzes data to evaluate the hypothesis. Statistical tests are often used to determine if the data supports or refutes the hypothesis.

Conclusion : Based on the analysis of the data, the researcher draws conclusions about the hypothesis. The hypothesis is either supported or rejected, leading to further research or new questions.

Remember, the hypothesis is not a one-time thing. It evolves throughout the research process, integrating new knowledge and findings.

What is the Process of Hypothesis Testing

Hypothesis testing involves a systematic process to assess the validity of a hypothesis. Here’s a simplified overview:

State the Hypotheses : Clearly articulate the null and alternative hypotheses based on your research question and expected outcomes.

Collect Data : Gather relevant data through surveys, observations, or experiments, depending on your research design.

Analyze Data : Apply appropriate statistical analyses to your data, comparing it to the expected outcomes.

Determine Significance : Assess the statistical significance of your findings. If the p-value is below a predetermined threshold (often 0.05), you can reject the null hypothesis and support the alternative hypothesis.

Draw Conclusions : Based on the analysis, draw conclusions regarding the hypothesis and its implications for your research.

Remember, hypothesis testing is a crucial step in the scientific process, providing evidence to support or refute theories.

How Many Steps are Required to Conduct a Hypothesis Testing

Hypothesis testing typically involves the following four steps:

Formulate Hypotheses : Articulate the null and alternative hypotheses that reflect your research question and predicted outcomes accurately.

Choose a Significance Level : Determine the desired level of significance (usually 0.05), representing the probability of obtaining results as extreme as those observed, assuming the null hypothesis is true.

Collect and Analyze Data : Gather data through experiments or observations, then analyze it using appropriate statistical tests, such as t-tests or chi-square tests.

Interpret Results : Evaluate the results and determine whether the data supports or refutes the null hypothesis. Consider the p-value, confidence intervals, and effect size when interpreting results.

Don’t let these steps intimidate you – they are the building blocks of scientific inquiry and help ensure robust conclusions.

What are the Key Characteristics of a Good Hypothesis

A good hypothesis possesses several key characteristics worth mentioning:

Testability : A hypothesis needs to be testable through empirical evidence, allowing researchers to gather data and substantiate it scientifically.

Specificity : A good hypothesis is precise and specific, leaving no room for ambiguity or misinterpretation. It focuses on a well-defined relationship between variables.

Relevance : A hypothesis should address a relevant research question or problem, contributing to the existing knowledge base in the field.

Logical Coherence : There should be a logical connection between the proposed relationship and any supporting evidence or theoretical framework.

Keep these characteristics in mind when crafting your hypothesis, and you’ll be well on your way to conducting sound research.

What are the 4 Steps of Hypothesis Testing

State the Hypotheses : Clearly articulate the null and alternative hypotheses, representing the current understanding and the researcher’s prediction, respectively.

Determine the Test Statistic : Select an appropriate test statistic based on the research question and type of data you’re analyzing.

Calculate the p-value : Calculate the p-value, which represents the probability of obtaining results as extreme as those observed, assuming the null hypothesis is true.

Conclusion : Compare the calculated p-value to the predefined significance level to determine whether to reject or fail to reject the null hypothesis. Make sure to interpret the results in the context of your research question.

These steps form the backbone of hypothesis testing, allowing you to draw meaningful conclusions based on statistical evidence.

Congratulations on making it to the end of our FAQ on the three required parts of a hypothesis! We’ve covered everything from the requirements of a hypothesis to types of hypotheses and even the stages of hypothesis testing. Armed with this knowledge, you’re ready to tackle your research projects with confidence. Remember, hypotheses are the backbone of scientific inquiry, so take your time to craft them, test them, and embrace the exciting process of discovery. Happy researching!

Disclaimer: This article is for informational purposes only and should not be considered as professional advice. Always consult with a qualified researcher before conducting any experiments or research studies.

• hypothesis testing
• independent variables
• mere statement
• null hypothesis
• observations
• research process
• research study
• scientific research

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Doing Research in the Real World

Student resources, multiple choice quiz.

Take the quiz to test your understanding of the key concepts covered in the chapter. Try testing yourself before you read the chapter to see where your strengths and weaknesses are, then test yourself again once you’ve read the chapter to see how well you’ve understood.

Tip: Click on each link to expand and view the content. Click again to collapse.

PART A: PRINCIPLES AND PLANNING FOR RESEARCH

1. Which of the following should not be a criterion for a good research project?

• Demonstrates the abilities of the researcher
• Is dependent on the completion of other projects
• Demonstrates the integration of different fields of knowledge
• Develops the skills of the researcher

b.  Is dependent on the completion of other projects

2. Which form of reasoning is the process of drawing a specific conclusion from a set of premises?

• Objective reasoning
• Positivistic reasoning
• Inductive reasoning
• Deductive reasoning

d:  Deductive reasoning

3. Research that seeks to examine the findings of a study by using the same design but a different sample is which of the following?

• An exploratory study
• A replication study
• An empirical study
• Hypothesis testing

b:  A replication study

4. A researcher designs an experiment to test how variables interact to influence job-seeking behaviours. The main purpose of the study was:

• Description
• Exploration
• Explanation

d:  Explanation

5. Cyber bullying at work is a growing threat to employee job satisfaction. Researchers want to find out why people do this and how they feel about it. The primary purpose of the study is:

c:  Exploration

6. A theory: 

• Is an accumulated body of knowledge
• Includes inconsequential ideas
• Is independent of research methodology
• Should be viewed uncritically

a:  Is an accumulated body of knowledge

7. Which research method is a bottom-up approach to research?

• Deductive method
• Explanatory method
• Inductive method
• Exploratory method

c:  Inductive method

8. How much confidence should you place in a single research study?

• You should trust research findings after different researchers have replicated the findings
• You should completely trust a single research study
• Neither a nor b
• Both a and b 

a:  You should trust research findings after different researchers have replicated the findings

9. A qualitative research problem statement:

• Specifies the research methods to be utilized
• Specifies a research hypothesis
• Expresses a relationship between variables
• Conveys a sense of emerging design

d:  Conveys a sense of emerging design

10. Which of the following is a good research question?

• To produce a report on student job searching behaviours
• To identify the relationship between self-efficacy and student job searching behaviours
• Students with higher levels of self-efficacy will demonstrate more active job searching behaviours
• Do students with high levels of self-efficacy demonstrate more active job searching behaviours?

d:  Do students with high levels of self-efficacy demonstrate more active job searching behaviours?

11. A review of the literature prior to formulating research questions allows the researcher to :

• Provide an up-to-date understanding of the subject, its significance, and structure
• Guide the development of research questions
• Present the kinds of research methodologies used in previous studies
• All of the above

d:  All of the above

12. Sometimes a comprehensive review of the literature prior to data collection is not recommended by:

• Ethnomethodology
• Grounded theory
• Symbolic interactionism
• Feminist theory

b:  Grounded theory

13. The feasibility of a research study should be considered in light of: 

• Cost and time required to conduct the study
• Access to gatekeepers and respondents
• Potential ethical concerns

14. Research that uses qualitative methods for one phase and quantitative methods for the next phase is known as:

• Action research
• Mixed-method research
• Quantitative research
• Pragmatic research

b:  Mixed-method research

15. Research hypotheses are:

• Formulated prior to a review of the literature
• Statements of predicted relationships between variables
• B but not A
• Both A and B

c:  B but not A

16. Which research approach is based on the epistemological viewpoint of pragmatism? 

• Qualitative research
• Mixed-methods research

c:  Mixed-methods research

17. Adopting ethical principles in research means: 

• Avoiding harm to participants
• The researcher is anonymous
• Deception is only used when necessary
• Selected informants give their consent

a:  Avoiding harm to participants

18. A radical perspective on ethics suggests that: 

• Researchers can do anything they want
• The use of checklists of ethical actions is essential
• The powers of Institutional Review Boards should be strengthened
• Ethics should be based on self-reflexivity

d:  Ethics should be based on self-reflexivity

19. Ethical problems can arise when researching the Internet because:

• Everyone has access to digital media
• Respondents may fake their identities
• Researchers may fake their identities
• Internet research has to be covert

b:  Respondents may fake their identities

20. The Kappa statistic: 

• Is a measure of inter-judge validity
• Compares the level of agreement between two judges against what might have been predicted by chance
• Ranges from 0 to +1
• Is acceptable above a score of 0.5

b:  Compares the level of agreement between two judges against what might have been predicted by chance

PART B: RESEARCH METHODOLOGY  

1. Which research paradigm is most concerned about generalizing its findings? 

a:  Quantitative research

2. A variable that is presumed to cause a change in another variable is called:

• An intervening variable
• A dependent variable
• An independent variable
• A numerical variable

c:  An independent variable

3. A study of teaching professionals posits that their performance-related pay increases their motivation which in turn leads to an increase in their job satisfaction. What kind of variable is ‘motivation”’ in this study? 

• Extraneous 
• Confounding
• Intervening
• Manipulated

c:  Intervening

4. Which correlation is the strongest? 

5. When interpreting a correlation coefficient expressing the relationship between two variables, it is important not to:

• Assume causality
• Measure the values for X and Y independently
• Choose X and Y values that are normally distributed
• Check the direction of the relationship

a:  Assume causality

6. Which of the following can be described as a nominal variable? 

• Annual income
• Annual sales
• Geographical location of a firm

d:  Geographical location of a firm

7. A positive correlation occurs when:

• Two variables remain constant
• Two variables move in the same direction
• One variable goes up and the other goes down
• Two variables move in opposite directions

b:  Two variables move in the same direction

8. The key defining characteristic of experimental research is that:

• The independent variable is manipulated
• Hypotheses are proved
• A positive correlation exists
• Samples are large

a:  The independent variable is manipulated

9. Qualitative research is used in all the following circumstances, EXCEPT:

• It is based on a collection of non-numerical data such as words and pictures
• It often uses small samples
• It uses the inductive method
• It is typically used when a great deal is already known about the topic of interest

d:  It is typically used when a great deal is already known about the topic of interest

10. In an experiment, the group that does not receive the intervention is called:

• The experimental group
• The participant group
• The control group
• The treatment group

c:  The control group

11. Which generally cannot be guaranteed in conducting qualitative studies in the field? 

• Keeping participants from physical and emotional harm
• Gaining informed consent
• Assuring anonymity rather than just confidentiality
• Maintaining consent forms

c:  Assuring anonymity rather than just confidentiality

12. Which of the following is not ethical practice in research with humans? 

• Maintaining participants’ anonymity
• Informing participants that they are free to withdraw at any time
• Requiring participants to continue until the study has been completed

d:  Requiring participants to continue until the study has been completed

13. What do we call data that are used for a new study but which were collected by an earlier researcher for a different set of research questions?

• Secondary data
• Field notes
• Qualitative data
• Primary data

a:  Secondary data

14. When each member of a population has an equal chance of being selected, this is called:

• A snowball sample
• A stratified sample
• A random probability sample
• A non-random sample

c:  A random probability sample

15. Which of the following techniques yields a simple random sample of hospitals?

• Randomly selecting a district and then sampling all hospitals within the district
• Numbering all the elements of a hospital sampling frame and then using a random number generator to pick hospitals from the table
• Listing hospitals by sector and choosing a proportion from within each sector at random
• Choosing volunteer hospitals to participate

b:  Numbering all the elements of a hospital sampling frame and then using a random number generator to pick hospitals from the table

16. Which of the following statements are true?

• The larger the sample size, the larger the confidence interval
• The smaller the sample size, the greater the sampling error
• The more categories being measured, the smaller the sample size
• A confidence level of 95 percent is always sufficient

b:  The smaller the sample size, the greater the sampling error

17. Which of the following will produce the least sampling error?

• A large sample based on convenience sampling 
• A small sample based on random sampling
• A large snowball sample
• A large sample based on random sampling

d:  A large sample based on random sampling

18. When people are readily available, volunteer, or are easily recruited to the sample, this is called:

• Snowball sampling
• Convenience sampling
• Stratified sampling
• Random sampling

b:  Convenience sampling

19. In qualitative research, sampling that involves selecting diverse cases is referred to as:

• Typical-case sampling
• Critical-case sampling
• Intensity sampling
• Maximum variation sampling

d:  Maximum variation sampling

20. A test accurately indicates an employee’s scores on a future criterion (e.g., conscientiousness).  What kind of validity is this?

a:  Predictive

PART C: DATA COLLECTION METHODS  

1. When designing a questionnaire it is important to do each of the following EXCEPT

• Pilot the questionnaire
• Avoid jargon
• Avoid double questions
• Use leading questions

d:  Use leading questions

2. One advantage of using a questionnaire is that:

• Probe questions can be asked
• Respondents can be put at ease
• Interview bias can be avoided
• Response rates are always high

c:  Interview bias can be avoided

3. Which of the following is true of observations?

• It takes less time than interviews
• It is often not possible to determine exactly why people behave as they do
• Covert observation raises fewer ethical concerns than overt

b:  It is often not possible to determine exactly why people behave as they do

4. A researcher secretly becomes an active member of a group in order to observe their behaviour. This researcher is acting as:

• An overt participant observer
• A covert non-participant observer
• A covert participant observer
• None of the above

c:  A covert participant observer

5. All of the following are advantages of structured observation, EXCEPT:

• Results can be replicated at a different time
• The coding schedule might impose a framework on what is being observed
• Data can be collected that participants may not realize is important
• Data do not have to rely on the recall of participants

b:  The coding schedule might impose a framework on what is being observed

6. When conducting an interview, asking questions such as: "What else? or ‘Could you expand on that?’ are all forms of:

• Structured responses
• Category questions

7. Secondary data can include which of the following? 

• Government statistics
• Personal diaries
• Organizational records

8. An ordinal scale is:

• The simplest form of measurement
• A scale with an absolute zero point
• A rank-order scale of measurement
• A scale with equal intervals between ranks

c:  A rank-order scale of measurement

9. Which term measures the extent to which scores from a test can be used to infer or predict performance in some activity? 

• Face validity
• Content reliability
• Criterion-related validity
• Construct validity

c:  Criterion-related validity

10. The ‘reliability’of a measure refers to the researcher asking:

• Does it give consistent results?
• Does it measure what it is supposed to measure?
• Can the results be generalized?
• Does it have face reliability?

a:  Does it give consistent results?

11. Interviewing is the favoured approach EXCEPT when:

• There is a need for highly personalized data
• It is important to ask supplementary questions
• High numbers of respondents are needed
• Respondents have difficulty with written language

c:  High numbers of respondents are needed

12. Validity in interviews is strengthened by the following EXCEPT:

• Building rapport with interviewees
• Multiple questions cover the same theme
• Constructing interview schedules that contain themes drawn from the literature
• Prompting respondents to expand on initial responses

b:  Multiple questions cover the same theme

13. Interview questions should:

• Lead the respondent
• Probe sensitive issues
• Be delivered in a neutral tone
• Test the respondents’ powers of memory

c:  Be delivered in a neutral tone

14. Active listening skills means:

• Asking as many questions as possible
• Avoiding silences
• Keeping to time
• Attentive listening

d:  Attentive listening

15. All the following are strengths of focus groups EXCEPT:

• They allow access to a wide range of participants
• Discussion allows for the validation of ideas and views
• They can generate a collective perspective
• They help maintain confidentiality

d:  They help maintain confidentiality

16. Which of the following is not always true about focus groups?

• The ideal size is normally between 6 and 12 participants
• Moderators should introduce themselves to the group
• Participants should come from diverse backgrounds
• The moderator poses preplanned questions

c:  Participants should come from diverse backgrounds

17. A disadvantage of using secondary data is that:

• The data may have been collected with reference to research questions that are not those of the researcher
• The researcher may bring more detachment in viewing the data than original researchers could muster
• Data have often been collected by teams of experienced researchers
• Secondary data sets are often available and accessible

a:  The data may have been collected with reference to research questions that are not those of the researcher

18. All of the following are sources of secondary data EXCEPT:

• Official statistics
• A television documentary
• The researcher’s research diary
• A company’s annual report

c:  The researcher’s research diary

19. Which of the following is not true about visual methods?

• They are not reliant on respondent recall
• The have low resource requirements
• They do not rely on words to capture what is happening
• They can capture what is happening in real time

b:  The have low resource requirements

20. Avoiding naïve empiricism in the interpretation of visual data means:

• Understanding the context in which they were produced
• Ensuring that visual images such as photographs are accurately taken
• Only using visual images with other data gathering sources
• Planning the capture of visual data carefully

a:  Understanding the context in which they were produced

PART D: ANALYSIS AND REPORT WRITING  

1. Which of the following is incorrect when naming a variable in SPSS?

• Must begin with a letter and not a number
• Must end in a full stop
• Cannot exceed 64 characters
• Cannot include symbols such as ?, & and %

b:  Must end in a full stop

2. Which of the following is not an SPSS Type variable?

3. A graph that uses vertical bars to represent data is called:

• A bar chart
• A pie chart
• A line graph
• A vertical graph

a:  A bar chart

4. The purpose of descriptive statistics is to:

• Summarize the characteristics of a data set
• Draw conclusions from the data

a:  Summarize the characteristics of a data set

5. The measure of the extent to which responses vary from the mean is called:

• The normal distribution
• The standard deviation
• The variance

c:  The standard deviation

6. To compare the performance of a group at time T1 and then at T2, we would use:

• A chi-squared test
• One-way analysis of variance
• Analysis of variance
• A paired t-test

d:  A paired t-test

7. A Type 1 error occurs in a situation where:

• The null hypothesis is accepted when it is in fact true
• The null hypothesis is rejected when it is in fact false
• The null hypothesis is rejected when it is in fact true
• The null hypothesis is accepted when it is in fact false

c:  The null hypothesis is rejected when it is in fact true

8. The significance level

• Is set after a statistical test is conducted
• Is always set at 0.05
• Results in a p -value
• Measures the probability of rejecting a true null hypothesis

d:  Measures the probability of rejecting a true null hypothesis

9. To predict the value of the dependent variable for a new case based on the knowledge of one or more independent variables, we would use

• Regression analysis
• Correlation analysis
• Kolmogorov-Smirnov test

a:  Regression analysis

10. In conducting secondary data analysis, researchers should ask themselves all of the following EXCEPT:

• Who produced the document?
• Is the material genuine?
• How can respondents be re-interviewed?
• Why was the document produced?

c:  How can respondents be re-interviewed?

11. Which of the following are not true of reflexivity?

• It recognizes that the researcher is not a neutral observer
• It has mainly been applied to the analysis of qualitative data
• It is part of a post-positivist tradition
• A danger of adopting a reflexive stance is the researcher can become the focus of the study

c:  It is part of a post-positivist tradition

12. Validity in qualitative research can be strengthened by all of the following EXCEPT:

• Member checking for accuracy and interpretation
• Transcribing interviews to improve accuracy of data
• Exploring rival explanations
• Analysing negative cases

b:  Transcribing interviews to improve accuracy of data

13. Qualitative data analysis programs are useful for each of the following EXCEPT: 

• Manipulation of large amounts of data
• Exploring of the data against new dimensions
• Querying of data
• Generating codes

d:  Generating codes

14. Which part of a research report contains details of how the research was planned and conducted?

• Introduction

b:  Design 

15. Which of the following is a form of research typically conducted by managers and other professionals to address issues in their organizations and/or professional practice?

• Basic research
• Professional research
• Predictive research

a:  Action research

16. Plagiarism can be avoided by:

• Copying the work of others accurately
• Paraphrasing the author’s text in your own words
• Cut and pasting from the Internet
• Quoting directly without revealing the source

b:  Paraphrasing the author’s text in your own words

17. In preparing for a presentation, you should do all of the following EXCEPT:

• Practice the presentation
• Ignore your nerves
• Get to know more about your audience
• Take an advanced look, if possible, at the facilities

b:  Ignore your nerves

18. You can create interest in your presentation by:

• Using bullet points
• Reading from notes
• Maximizing the use of animation effects
• Using metaphors

d:  Using metaphors

19. In preparing for a viva or similar oral examination, it is best if you have:

• Avoided citing the examiner in your thesis
• Made exaggerated claims on the basis of your data
• Published and referenced your own article(s)
• Tried to memorize your work

c:  Published and referenced your own article(s)

20. Grounded theory coding:

• Makes use of a priori concepts from the literature
• Uses open coding, selective coding, then axial coding
• Adopts a deductive stance
• Stops when theoretical saturation has been reached

d:  Stops when theoretical saturation has been reached

What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples

By:  Derek Jansen (MBA)  | Reviewed By: Dr Eunice Rautenbach | June 2020

If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .

“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing. 

Research Hypothesis 101

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

What is a hypothesis?

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

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

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

Hypothesis: sleep impacts academic performance.

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

But that’s not good enough…

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

What is a research hypothesis?

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

Let’s take a look at these more closely.

Need a helping hand?

Hypothesis Essential #1: Specificity & Clarity

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

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

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

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

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

Hypothesis Essential #2: Testability (Provability)

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

For example, consider the hypothesis we mentioned earlier:

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

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

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

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

Defining A Research Hypothesis

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

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

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

What about the null hypothesis?

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

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

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

And there you have it – hypotheses in a nutshell. 

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

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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16 Comments

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

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

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

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

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

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

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

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

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

could you please elaborate it more

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

This is very helpful

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

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

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

this is very important note help me much more

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Published November 23, 2021. Updated December 13, 2021.

A hypothesis is a testable statement based on the researcher’s expectation for the outcome of a study or an observed phenomenon. It helps establish a relationship between two or more variables. A hypothesis acts as the objective of research and guides the researcher to structure experiments that would produce accurate and reliable results. In all likelihood, if a hypothesis is proven by repeatable and reproducible experiments, it may become a theory or even a law of nature.

What is a hypothesis?

A research hypothesis is an educated, clear, specific and falsifiable prediction of the possible outcomes of scientific observation. A hypothesis can be considered as the starting point of research, as any research without it is aimless. For a hypothesis to be complete, it should contain three main elements, i.e., two or more variables, a population, and the correlation between the variables. A hypothesis lays out a path for researchers, directing them how exactly the experiment should be designed, the type of data that should be collected, the sample size for the experiment, and how the data analysis should be performed, along with providing a basis to obtain results and validate them.

Observation and prior knowledge are the primary steps to developing a research hypothesis.  For example:

You are watching a race in school and observe the speed with which the winner ran. You may wonder why the winner ran so fast. You may think of a few possibilities which could lead to this result, such as the amount of practice before the race, hours of sleep, or consumption of an energy drink. Since the amount of practice and sleep may almost be constant for all the participants, you may feel the win is because of the consumption of an energy drink. So, you may develop a hypothesis such as “Athletes consuming an energy drink daily perform better.”

Developing a good hypothesis

A hypothesis is important as it helps predict the relationship between two variables, which is essential for conducting your research. In the previous example, the researcher uses the consumption of energy drinks and athlete performance as variables and the athletes as a population while trying to establish the effect of the consumption of an energy drink on the performance of an athlete.

A good hypothesis is central to research for providing reliable and valid results. There are a few points should be kept in mind while formulating your hypothesis. Let’s have a look at them.

1)  Ask a question : The foremost step to developing a hypothesis is asking a question. Identifying a question which you are interested in studying is important. For example:

How can air pollution in a region be reduced?

2) Conceptual nature : A hypothesis should be related to a certain concept. This allows the linking of research questions in a study, collecting data, and performing analysis according to the stated concept. For example:

Regions with a greater percentage of tree cover are likely to be less polluted than regions with lower tree cover.

3) Verbal statement : A hypothesis is phrased as a declaration and never as a question. It is the representation of the researcher’s idea or assumption in words that can be tested. For example:

Bad hypothesis: Does following a healthy diet alter the weight of a person?

Good hypothesis: People who follow a healthy diet stay fit.

4) Falsifiable and testable : A hypothesis should be testable so that experiments can be conducted to make observations that agree or disagree with it. It should be falsifiable so that it can be proven wrong if it is found to be incorrect. For example:

Children who use phones while studying score low marks in their exams.

5) Relationship between two variables : A hypothesis suggests a relationship between two or more variables. An independent variable is controlled by the researcher to look at the effects on other variables, i.e., it is the cause for something to happen. A dependent variable is affected by the independent variable and is observed and measured by the researcher. For example:

Consumption of aerated drinks leads to increased blood sugar levels.

Here, the consumption of aerated drinks is the independent variable. The dependent variable is the sugar level that is affected by the consumption of aerated drinks.

6) Specific and precise : A hypothesis should not be too general or vague as obtaining focused results becomes difficult. Also, a hypothesis should not be too specific as it limits the scope of the study. For example:

General: Eating food leads to weight gain.

Specific: Eating ice cream causes weight gain.

Good hypothesis: Consumption of sugar-rich food causes weight in individuals.

If these factors are paid attention to while structuring your hypothesis, you are sure to formulate a sound hypothesis that will direct your research down the correct path.

Types of hypotheses

The hypothesis can be classified into the following categories:

1) Simple Hypothesis : Simple hypotheses draw a relationship between a single independent variable and a single dependent variable. For example:

Increased hours of studying by students leads to them getting better marks.

Here, the hours of study acts as the independent variable while the obtained marks act as the dependent variable.

2) Complex Hypothesis : A complex hypothesis tends to propose a relationship between two or more independent and dependent variables. For example:

Increased hours of studying and eight hours of sleep by students result in getting better marks by an increased attention span.

3) Directional Hypothesis :  This type of hypothesis predicts the nature of the effect of an independent variable on the dependent variable, thus predicting the direction of the effect. For example:

Students scoring good marks in exams tend to have better jobs than the students who score low marks in exams.

Here both the effect and the direction of the effect are represented in the hypothesis.

4) Non-directional Hypothesis : The null hypothesis states a relationship between two variables but does not state the kind of effect that may exist between them. For example:

Students scoring good marks will have jobs different from students scoring low marks.

5) Null Hypothesis : This is a negative statement contrary to the hypothesis and suggests no relationship between the independent and the dependent variable. It is represented as H o . For example:

H o : There is no relationship between hours of study by a student and the earned marks.

H o : Students scoring good and low marks are likely to get similar jobs.

6) Alternative Hypothesis : An alternative to the null hypothesis, it suggests the difference or effect between two or more variables. It is represented as H 1 . For example:

H 1 : There is a relationship between hours of study by a student and the earned marks.

H 1 : Students scoring good and low marks are likely to get different quality jobs.

How to structure a hypothesis?

A hypothesis should be structured in such a way that it should be simple, clear, and easy to understand, and should represent the intent of the hypothesis. There are a few ways to do this:

1) A hypothesis can be represented as a simple ‘if…then’ statement. While the first part of the statement introduces the independent variable, the latter part brings up the dependent variable. For example:

If the plant is watered, then the plant’s growth will improve.

2) A hypothesis can also be written as a statement correlating two variables, directly predicting the relationship between the two variables. For example:

The more times a plant is watered, the better the growth of the plant will be.

3) Another way of structuring a hypothesis is to compare two groups and state the difference expected to occur between the two groups. For example:

Plants that are watered daily are taller than plants that are watered on alternate days.

Testing a hypothesis

Once you have formulated your hypothesis, the next step is to test it to determine if it is correct or incorrect.  The steps given below help to test a hypothesis:

1) State your research hypothesis in the form of a null hypothesis (H o ) and an alternative hypothesis (H 1 ).

2) Perform appropriate experiments and collect data to test the hypothesis.

3) Analyze the data to see whether the hypothesis is supported or refuted.

4) Interpret the data and present your results.

Key takeaways

• A hypothesis is a testable statement based on the researcher’s expectation of an outcome for observed phenomena that is simple, clear, specific, and focuses on only one issue.
• A hypothesis is the focal point of research and directs the course of the research in terms of data collection, sample size, and data analysis.
• A hypothesis is composed of three main components: two or more variables, a population, and the relationship between the variables. Independent and dependent variables are two kinds of variables used while structuring a hypothesis.
• It should be possible to test the hypothesis by performing experiments and prove it to be correct or incorrect.
• A hypothesis helps in testing theories, investigating activities, explaining social phenomena. Further, while acting as a bridge between theory and investigation, it helps determine the most suitable type of research for a problem and allows for the empirical testing of a relationship between variables. If you are lucky, one of your hypotheses may suggest a theory!

Research Process

For more details, visit these additional research guides .

Understand the Research Process

• Research process
• Research questions
• Operationalization
• Research problem
• Statement of the problem
• Background research
• Research hypothesis
• Generalization

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Chapter 14: The Research Proposal

14.3 Components of a Research Proposal

Krathwohl (2005) suggests and describes a variety of components to include in a research proposal. The following sections – Introductions, Background and significance, Literature Review; Research design and methods, Preliminary suppositions and implications; and Conclusion present these components in a suggested template for you to follow in the preparation of your research proposal.

Introduction

The introduction sets the tone for what follows in your research proposal – treat it as the initial pitch of your idea. After reading the introduction your reader should:

• understand what it is you want to do;
• have a sense of your passion for the topic; and
• be excited about the study’s possible outcomes.

As you begin writing your research proposal, it is helpful to think of the introduction as a narrative of what it is you want to do, written in one to three paragraphs. Within those one to three paragraphs, it is important to briefly answer the following questions:

• What is the central research problem?
• How is the topic of your research proposal related to the problem?
• What methods will you utilize to analyze the research problem?
• Why is it important to undertake this research? What is the significance of your proposed research? Why are the outcomes of your proposed research important? Whom are they important?

Note : You may be asked by your instructor to include an abstract with your research proposal. In such cases, an abstract should provide an overview of what it is you plan to study, your main research question, a brief explanation of your methods to answer the research question, and your expected findings. All of this information must be carefully crafted in 150 to 250 words. A word of advice is to save the writing of your abstract until the very end of your research proposal preparation. If you are asked to provide an abstract, you should include 5 to 7 key words that are of most relevance to your study. List these in order of relevance.

Background and significance

The purpose of this section is to explain the context of your proposal and to describe, in detail, why it is important to undertake this research. Assume that the person or people who will read your research proposal know nothing or very little about the research problem. While you do not need to include all knowledge you have learned about your topic in this section, it is important to ensure that you include the most relevant material that will help to explain the goals of your research.

While there are no hard and fast rules, you should attempt to address some or all of the following key points:

• State the research problem and provide a more thorough explanation about the purpose of the study than what you stated in the introduction.
• Present the rationale for the proposed research study. Clearly indicate why this research is worth doing. Answer the “so what?” question.
• Describe the major issues or problems to be addressed by your research. Do not forget to explain how and in what ways your proposed research builds upon previous related research.
• Explain how you plan to go about conducting your research.
• Clearly identify the key or most relevant sources of research you intend to use and explain how they will contribute to your analysis of the topic.
• Set the boundaries of your proposed research, in order to provide a clear focus. Where appropriate, state not only what you will study, but what will be excluded from your study.
• Provide clear definitions of key concepts and terms. Since key concepts and terms often have numerous definitions, make sure you state which definition you will be utilizing in your research.

Literature review

This key component of the research proposal is the most time-consuming aspect in the preparation of your research proposal. As described in Chapter 5 , the literature review provides the background to your study and demonstrates the significance of the proposed research. Specifically, it is a review and synthesis of prior research that is related to the problem you are setting forth to investigate. Essentially, your goal in the literature review is to place your research study within the larger whole of what has been studied in the past, while demonstrating to your reader that your work is original, innovative, and adds to the larger whole.

As the literature review is information dense, it is essential that this section be intelligently structured to enable your reader to grasp the key arguments underpinning your study. However, this can be easier to state and harder to do, simply due to the fact there is usually a plethora of related research to sift through. Consequently, a good strategy for writing the literature review is to break the literature into conceptual categories or themes, rather than attempting to describe various groups of literature you reviewed. Chapter 5   describes a variety of methods to help you organize the themes.

Here are some suggestions on how to approach the writing of your literature review:

• Think about what questions other researchers have asked, what methods they used, what they found, and what they recommended based upon their findings.
• Do not be afraid to challenge previous related research findings and/or conclusions.
• Assess what you believe to be missing from previous research and explain how your research fills in this gap and/or extends previous research.

It is important to note that a significant challenge related to undertaking a literature review is knowing when to stop. As such, it is important to know when you have uncovered the key conceptual categories underlying your research topic. Generally, when you start to see repetition in the conclusions or recommendations, you can have confidence that you have covered all of the significant conceptual categories in your literature review. However, it is also important to acknowledge that researchers often find themselves returning to the literature as they collect and analyze their data. For example, an unexpected finding may develop as you collect and/or analyze the data; in this case, it is important to take the time to step back and review the literature again, to ensure that no other researchers have found a similar finding. This may include looking to research outside your field.

This situation occurred with one of this textbook’s authors’ research related to community resilience. During the interviews, the researchers heard many participants discuss individual resilience factors and how they believed these individual factors helped make the community more resilient, overall. Sheppard and Williams (2016) had not discovered these individual factors in their original literature review on community and environmental resilience. However, when they returned to the literature to search for individual resilience factors, they discovered a small body of literature in the child and youth psychology field. Consequently, Sheppard and Williams had to go back and add a new section to their literature review on individual resilience factors. Interestingly, their research appeared to be the first research to link individual resilience factors with community resilience factors.

Research design and methods

The objective of this section of the research proposal is to convince the reader that your overall research design and methods of analysis will enable you to solve the research problem you have identified and also enable you to accurately and effectively interpret the results of your research. Consequently, it is critical that the research design and methods section is well-written, clear, and logically organized. This demonstrates to your reader that you know what you are going to do and how you are going to do it. Overall, you want to leave your reader feeling confident that you have what it takes to get this research study completed in a timely fashion.

Essentially, this section of the research proposal should be clearly tied to the specific objectives of your study; however, it is also important to draw upon and include examples from the literature review that relate to your design and intended methods. In other words, you must clearly demonstrate how your study utilizes and builds upon past studies, as it relates to the research design and intended methods. For example, what methods have been used by other researchers in similar studies?

While it is important to consider the methods that other researchers have employed, it is equally, if not more, important to consider what methods have not been but could be employed. Remember, the methods section is not simply a list of tasks to be undertaken. It is also an argument as to why and how the tasks you have outlined will help you investigate the research problem and answer your research question(s).

Tips for writing the research design and methods section:

Specify the methodological approaches you intend to employ to obtain information and the techniques you will use to analyze the data.

Specify the research operations you will undertake and the way you will interpret the results of those operations in relation to the research problem.

Go beyond stating what you hope to achieve through the methods you have chosen. State how you will actually implement the methods (i.e., coding interview text, running regression analysis, etc.).

Anticipate and acknowledge any potential barriers you may encounter when undertaking your research, and describe how you will address these barriers.

Explain where you believe you will find challenges related to data collection, including access to participants and information.

Preliminary suppositions and implications

The purpose of this section is to argue how you anticipate that your research will refine, revise, or extend existing knowledge in the area of your study. Depending upon the aims and objectives of your study, you should also discuss how your anticipated findings may impact future research. For example, is it possible that your research may lead to a new policy, theoretical understanding, or method for analyzing data? How might your study influence future studies? What might your study mean for future practitioners working in the field? Who or what might benefit from your study? How might your study contribute to social, economic or environmental issues? While it is important to think about and discuss possibilities such as these, it is equally important to be realistic in stating your anticipated findings. In other words, you do not want to delve into idle speculation. Rather, the purpose here is to reflect upon gaps in the current body of literature and to describe how you anticipate your research will begin to fill in some or all of those gaps.

The conclusion reiterates the importance and significance of your research proposal, and provides a brief summary of the entire proposed study. Essentially, this section should only be one or two paragraphs in length. Here is a potential outline for your conclusion:

Discuss why the study should be done. Specifically discuss how you expect your study will advance existing knowledge and how your study is unique.

Explain the specific purpose of the study and the research questions that the study will answer.

Explain why the research design and methods chosen for this study are appropriate, and why other designs and methods were not chosen.

State the potential implications you expect to emerge from your proposed study,

Provide a sense of how your study fits within the broader scholarship currently in existence, related to the research problem.

Citations and references

As with any scholarly research paper, you must cite the sources you used in composing your research proposal. In a research proposal, this can take two forms: a reference list or a bibliography. A reference list lists the literature you referenced in the body of your research proposal. All references in the reference list must appear in the body of the research proposal. Remember, it is not acceptable to say “as cited in …” As a researcher you must always go to the original source and check it for yourself. Many errors are made in referencing, even by top researchers, and so it is important not to perpetuate an error made by someone else. While this can be time consuming, it is the proper way to undertake a literature review.

In contrast, a bibliography , is a list of everything you used or cited in your research proposal, with additional citations to any key sources relevant to understanding the research problem. In other words, sources cited in your bibliography may not necessarily appear in the body of your research proposal. Make sure you check with your instructor to see which of the two you are expected to produce.

Overall, your list of citations should be a testament to the fact that you have done a sufficient level of preliminary research to ensure that your project will complement, but not duplicate, previous research efforts. For social sciences, the reference list or bibliography should be prepared in American Psychological Association (APA) referencing format. Usually, the reference list (or bibliography) is not included in the word count of the research proposal. Again, make sure you check with your instructor to confirm.

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

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What is Hypothesis? Definition, Meaning, Characteristics, Sources

• Post last modified: 10 January 2022
• Reading time: 18 mins read
• Post category: Research Methodology

• What is Hypothesis?

Hypothesis is a prediction of the outcome of a study. Hypotheses are drawn from theories and research questions or from direct observations. In fact, a research problem can be formulated as a hypothesis. To test the hypothesis we need to formulate it in terms that can actually be analysed with statistical tools.

As an example, if we want to explore whether using a specific teaching method at school will result in better school marks (research question), the hypothesis could be that the mean school marks of students being taught with that specific teaching method will be higher than of those being taught using other methods.

In this example, we stated a hypothesis about the expected differences between groups. Other hypotheses may refer to correlations between variables.

Table of Content

• 1 What is Hypothesis?
• 2 Hypothesis Definition
• 3 Meaning of Hypothesis
• 4.1 Conceptual Clarity
• 4.2 Need of empirical referents
• 4.3 Hypothesis should be specific
• 4.4 Hypothesis should be within the ambit of the available research techniques
• 4.5 Hypothesis should be consistent with the theory
• 4.6 Hypothesis should be concerned with observable facts and empirical events
• 4.7 Hypothesis should be simple
• 5.1 Observation
• 5.2 Analogies
• 5.4 State of Knowledge
• 5.5 Culture
• 5.6 Continuity of Research
• 6.1 Null Hypothesis
• 6.2 Alternative Hypothesis

Thus, to formulate a hypothesis, we need to refer to the descriptive statistics (such as the mean final marks), and specify a set of conditions about these statistics (such as a difference between the means, or in a different example, a positive or negative correlation). The hypothesis we formulate applies to the population of interest.

The null hypothesis makes a statement that no difference exists (see Pyrczak, 1995, pp. 75-84).

Hypothesis Definition

A hypothesis is ‘a guess or supposition as to the existence of some fact or law which will serve to explain a connection of facts already known to exist.’ – J. E. Creighton & H. R. Smart

Hypothesis is ‘a proposition not known to be definitely true or false, examined for the sake of determining the consequences which would follow from its truth.’ – Max Black

Hypothesis is ‘a proposition which can be put to a test to determine validity and is useful for further research.’ – W. J. Goode and P. K. Hatt

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

Meaning of Hypothesis

From the above mentioned definitions of hypothesis, its meaning can be explained in the following ways.

• At the primary level, a hypothesis is the possible and probable explanation of the sequence of happenings or data.
• Sometimes, hypothesis may emerge from an imagination, common sense or a sudden event.
• Hypothesis can be a probable answer to the research problem undertaken for study. 4. Hypothesis may not always be true. It can get disproven. In other words, hypothesis need not always be a true proposition.
• Hypothesis, in a sense, is an attempt to present the interrelations that exist in the available data or information.
• Hypothesis is not an individual opinion or community thought. Instead, it is a philosophical means which is to be used for research purpose. Hypothesis is not to be considered as the ultimate objective; rather it is to be taken as the means of explaining scientifically the prevailing situation.

The concept of hypothesis can further be explained with the help of some examples. Lord Keynes, in his theory of national income determination, made a hypothesis about the consumption function. He stated that the consumption expenditure of an individual or an economy as a whole is dependent on the level of income and changes in a certain proportion.

Later, this proposition was proved in the statistical research carried out by Prof. Simon Kuznets. Matthus, while studying the population, formulated a hypothesis that population increases faster than the supply of food grains. Population studies of several countries revealed that this hypothesis is true.

Validation of the Malthus’ hypothesis turned it into a theory and when it was tested in many other countries it became the famous Malthus’ Law of Population. It thus emerges that when a hypothesis is tested and proven, it becomes a theory. The theory, when found true in different times and at different places, becomes the law. Having understood the concept of hypothesis, few hypotheses can be formulated in the areas of commerce and economics.

• Population growth moderates with the rise in per capita income.
• Sales growth is positively linked with the availability of credit.
• Commerce education increases the employability of the graduate students.
• High rates of direct taxes prompt people to evade taxes.
• Good working conditions improve the productivity of employees.
• Advertising is the most effecting way of promoting sales than any other scheme.
• Higher Debt-Equity Ratio increases the probability of insolvency.
• Economic reforms in India have made the public sector banks more efficient and competent.
• Foreign direct investment in India has moved in those sectors which offer higher rate of profit.
• There is no significant association between credit rating and investment of fund.

Characteristics of Hypothesis

Not all the hypotheses are good and useful from the point of view of research. It is only a few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken. The characteristics of such a useful hypothesis can be listed as below:

Conceptual Clarity

Need of empirical referents, hypothesis should be specific, hypothesis should be within the ambit of the available research techniques, hypothesis should be consistent with the theory, hypothesis should be concerned with observable facts and empirical events, hypothesis should be simple.

The concepts used while framing hypothesis should be crystal clear and unambiguous. Such concepts must be clearly defined so that they become lucid and acceptable to everyone. How are the newly developed concepts interrelated and how are they linked with the old one is to be very clear so that the hypothesis framed on their basis also carries the same clarity.

A hypothesis embodying unclear and ambiguous concepts can to a great extent undermine the successful completion of the research work.

A hypothesis can be useful in the research work undertaken only when it has links with some empirical referents. Hypothesis based on moral values and ideals are useless as they cannot be tested. Similarly, hypothesis containing opinions as good and bad or expectation with respect to something are not testable and therefore useless.

For example, ‘current account deficit can be lowered if people change their attitude towards gold’ is a hypothesis encompassing expectation. In case of such a hypothesis, the attitude towards gold is something which cannot clearly be described and therefore a hypothesis which embodies such an unclean thing cannot be tested and proved or disproved. In short, the hypothesis should be linked with some testable referents.

For the successful conduction of research, it is necessary that the hypothesis is specific and presented in a precise manner. Hypothesis which is general, too ambitious and grandiose in scope is not to be made as such hypothesis cannot be easily put to test. A hypothesis is to be based on such concepts which are precise and empirical in nature. A hypothesis should give a clear idea about the indicators which are to be used.

For example, a hypothesis that economic power is increasingly getting concentrated in a few hands in India should enable us to define the concept of economic power. It should be explicated in terms of measurable indicator like income, wealth, etc. Such specificity in the formulation of a hypothesis ensures that the research is practicable and significant.

While framing the hypothesis, the researcher should be aware of the available research techniques and should see that the hypothesis framed is testable on the basis of them. In other words, a hypothesis should be researchable and for this it is important that a due thought has been given to the methods and techniques which can be used to measure the concepts and variables embodied in the hypothesis.

It does not however mean that hypotheses which are not testable with the available techniques of research are not to be made. If the problem is too significant and therefore the hypothesis framed becomes too ambitious and complex, it’s testing becomes possible with the development of new research techniques or the hypothesis itself leads to the development of new research techniques.

A hypothesis must be related to the existing theory or should have a theoretical orientation. The growth of knowledge takes place in the sequence of facts, hypothesis, theory and law or principles. It means the hypothesis should have a correspondence with the existing facts and theory.

If the hypothesis is related to some theory, the research work will enable us to support, modify or refute the existing theory. Theoretical orientation of the hypothesis ensures that it becomes scientifically useful. According to Prof. Goode and Prof. Hatt, research work can contribute to the existing knowledge only when the hypothesis is related with some theory.

This enables us to explain the observed facts and situations and also verify the framed hypothesis. In the words of Prof. Cohen and Prof. Nagel, “hypothesis must be formulated in such a manner that deduction can be made from it and that consequently a decision can be reached as to whether it does or does not explain the facts considered.”

If the research work based on a hypothesis is to be successful, it is necessary that the later is as simple and easy as possible. An ambition of finding out something new may lead the researcher to frame an unrealistic and unclear hypothesis. Such a temptation is to be avoided. Framing a simple, easy and testable hypothesis requires that the researcher is well acquainted with the related concepts.

Sources of Hypothesis

Hypotheses can be derived from various sources. Some of the sources is given below:

Observation

State of knowledge, continuity of research.

Hypotheses can be derived from observation from the observation of price behavior in a market. For example the relationship between the price and demand for an article is hypothesized.

Analogies are another source of useful hypotheses. Julian Huxley has pointed out that casual observations in nature or in the framework of another science may be a fertile source of hypotheses. For example, the hypotheses that similar human types or activities may be found in similar geophysical regions come from plant ecology.

This is one of the main sources of hypotheses. It gives direction to research by stating what is known logical deduction from theory lead to new hypotheses. For example, profit / wealth maximization is considered as the goal of private enterprises. From this assumption various hypotheses are derived’.

An important source of hypotheses is the state of knowledge in any particular science where formal theories exist hypotheses can be deduced. If the hypotheses are rejected theories are scarce hypotheses are generated from conception frameworks.

Another source of hypotheses is the culture on which the researcher was nurtured. Western culture has induced the emergence of sociology as an academic discipline over the past decade, a large part of the hypotheses on American society examined by researchers were connected with violence. This interest is related to the considerable increase in the level of violence in America.

The continuity of research in a field itself constitutes an important source of hypotheses. The rejection of some hypotheses leads to the formulation of new ones capable of explaining dependent variables in subsequent research on the same subject.

Null and Alternative Hypothesis

Null hypothesis.

The hypothesis that are proposed with the intent of receiving a rejection for them are called Null Hypothesis . This requires that we hypothesize the opposite of what is desired to be proved. For example, if we want to show that sales and advertisement expenditure are related, we formulate the null hypothesis that they are not related.

Similarly, if we want to conclude that the new sales training programme is effective, we formulate the null hypothesis that the new training programme is not effective, and if we want to prove that the average wages of skilled workers in town 1 is greater than that of town 2, we formulate the null hypotheses that there is no difference in the average wages of the skilled workers in both the towns.

Since we hypothesize that sales and advertisement are not related, new training programme is not effective and the average wages of skilled workers in both the towns are equal, we call such hypotheses null hypotheses and denote them as H 0 .

Alternative Hypothesis

Rejection of null hypotheses leads to the acceptance of alternative hypothesis . The rejection of null hypothesis indicates that the relationship between variables (e.g., sales and advertisement expenditure) or the difference between means (e.g., wages of skilled workers in town 1 and town 2) or the difference between proportions have statistical significance and the acceptance of the null hypotheses indicates that these differences are due to chance.

As already mentioned, the alternative hypotheses specify that values/relation which the researcher believes hold true. The alternative hypotheses can cover a whole range of values rather than a single point. The alternative hypotheses are denoted by H 1 .

Business Ethics

( Click on Topic to Read )

• What is Ethics?
• What is Business Ethics?
• Values, Norms, Beliefs and Standards in Business Ethics
• Indian Ethos in Management
• Ethical Issues in Marketing
• Ethical Issues in HRM
• Ethical Issues in IT
• Ethical Issues in Production and Operations Management
• Ethical Issues in Finance and Accounting
• What is Corporate Governance?
• What is Ownership Concentration?
• What is Ownership Composition?
• Types of Companies in India
• Internal Corporate Governance
• External Corporate Governance
• Corporate Governance in India
• What is Enterprise Risk Management (ERM)?
• What is Assessment of Risk?
• What is Risk Register?
• Risk Management Committee

Corporate social responsibility (CSR)

• Theories of CSR
• Arguments Against CSR
• Business Case for CSR
• Importance of CSR in India
• Drivers of Corporate Social Responsibility
• Developing a CSR Strategy
• Implement CSR Commitments
• CSR Marketplace
• CSR at Workplace
• Environmental CSR
• CSR with Communities and in Supply Chain
• Community Interventions
• CSR Monitoring
• CSR Reporting
• Voluntary Codes in CSR
• What is Corporate Ethics?

Lean Six Sigma

• What is Six Sigma?
• What is Lean Six Sigma?
• Value and Waste in Lean Six Sigma
• Six Sigma Team
• MAIC Six Sigma
• Six Sigma in Supply Chains
• What is Binomial, Poisson, Normal Distribution?
• What is Sigma Level?
• What is DMAIC in Six Sigma?
• What is DMADV in Six Sigma?
• Six Sigma Project Charter
• Project Decomposition in Six Sigma
• Critical to Quality (CTQ) Six Sigma
• Process Mapping Six Sigma
• Flowchart and SIPOC
• Gage Repeatability and Reproducibility
• Statistical Diagram
• Lean Techniques for Optimisation Flow
• Failure Modes and Effects Analysis (FMEA)
• What is Process Audits?
• Six Sigma Implementation at Ford
• IBM Uses Six Sigma to Drive Behaviour Change
• Research Methodology
• What is Research?
• Sampling Method
• Research Methods

Data Collection in Research

• Methods of Collecting Data
• Application of Business Research
• Levels of Measurement
• What is Sampling?
• Hypothesis Testing

Research Report

• What is Management?
• Planning in Management
• Decision Making in Management
• What is Controlling?
• What is Coordination?
• What is Staffing?
• Organization Structure
• What is Departmentation?
• Span of Control
• What is Authority?
• Centralization vs Decentralization
• Organizing in Management
• Schools of Management Thought
• Classical Management Approach
• Is Management an Art or Science?
• Who is a Manager?

Operations Research

• What is Operations Research?
• Operation Research Models
• Linear Programming
• Linear Programming Graphic Solution
• Linear Programming Simplex Method
• Linear Programming Artificial Variable Technique
• Duality in Linear Programming
• Transportation Problem Initial Basic Feasible Solution
• Transportation Problem Finding Optimal Solution
• Project Network Analysis with Critical Path Method
• Project Network Analysis Methods
• Project Evaluation and Review Technique (PERT)
• Simulation in Operation Research
• Replacement Models in Operation Research

Operation Management

• What is Strategy?
• What is Operations Strategy?
• Operations Competitive Dimensions
• Operations Strategy Formulation Process
• What is Strategic Fit?
• Strategic Design Process
• Focused Operations Strategy
• Corporate Level Strategy
• Expansion Strategies
• Stability Strategies
• Retrenchment Strategies
• Competitive Advantage
• Strategic Choice and Strategic Alternatives
• What is Production Process?
• What is Process Technology?
• What is Process Improvement?
• Strategic Capacity Management
• Production and Logistics Strategy
• Taxonomy of Supply Chain Strategies
• Factors Considered in Supply Chain Planning
• Operational and Strategic Issues in Global Logistics
• Logistics Outsourcing Strategy
• What is Supply Chain Mapping?
• Supply Chain Process Restructuring
• Points of Differentiation
• Re-engineering Improvement in SCM
• What is Supply Chain Drivers?
• Supply Chain Operations Reference (SCOR) Model
• Customer Service and Cost Trade Off
• Internal and External Performance Measures
• Linking Supply Chain and Business Performance
• Netflix’s Niche Focused Strategy
• Disney and Pixar Merger
• Process Planning at Mcdonald’s

Service Operations Management

• What is Service?
• What is Service Operations Management?
• What is Service Design?
• Service Design Process
• Service Delivery
• What is Service Quality?
• Gap Model of Service Quality
• Juran Trilogy
• Service Performance Measurement
• Service Decoupling
• IT Service Operation
• Service Operations Management in Different Sector

Procurement Management

• What is Procurement Management?
• Procurement Negotiation
• Types of Requisition
• RFX in Procurement
• What is Purchasing Cycle?
• Vendor Managed Inventory
• Internal Conflict During Purchasing Operation
• Spend Analysis in Procurement
• Sourcing in Procurement
• Supplier Evaluation and Selection in Procurement
• Blacklisting of Suppliers in Procurement
• Total Cost of Ownership in Procurement
• Incoterms in Procurement
• Documents Used in International Procurement
• Transportation and Logistics Strategy
• What is Capital Equipment?
• Procurement Process of Capital Equipment
• Acquisition of Technology in Procurement
• What is E-Procurement?
• E-marketplace and Online Catalogues
• Fixed Price and Cost Reimbursement Contracts
• Contract Cancellation in Procurement
• Ethics in Procurement
• Legal Aspects of Procurement
• Global Sourcing in Procurement
• Intermediaries and Countertrade in Procurement

Strategic Management

• What is Strategic Management?
• What is Value Chain Analysis?
• Mission Statement
• Business Level Strategy
• What is SWOT Analysis?
• What is Competitive Advantage?
• What is Vision?
• What is Ansoff Matrix?
• Prahalad and Gary Hammel
• Strategic Management In Global Environment
• Competitor Analysis Framework
• Competitive Rivalry Analysis
• Competitive Dynamics
• What is Competitive Rivalry?
• Five Competitive Forces That Shape Strategy
• What is PESTLE Analysis?
• Fragmentation and Consolidation Of Industries
• What is Technology Life Cycle?
• What is Diversification Strategy?
• What is Corporate Restructuring Strategy?
• Resources and Capabilities of Organization
• Role of Leaders In Functional-Level Strategic Management
• Functional Structure In Functional Level Strategy Formulation
• Information And Control System
• What is Strategy Gap Analysis?
• Issues In Strategy Implementation
• Matrix Organizational Structure
• What is Strategic Management Process?

Supply Chain

• What is Supply Chain Management?
• Supply Chain Planning and Measuring Strategy Performance
• What is Warehousing?
• What is Packaging?
• What is Inventory Management?
• What is Material Handling?
• What is Order Picking?
• Receiving and Dispatch, Processes
• What is Warehouse Design?
• What is Warehousing Costs?

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Write a Research Proposal

Structure and content, introduction (to topic and problem), research question (or hypothesis, thesis statement, aim), proposed methodology, anticipated findings, contributions - impact and significance, tables and figures (if applicable).

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The structure and content of a research proposal can vary depending upon the discipline, purpose, and target audience. For example, a graduate thesis proposal and a Tri-Council grant proposal will have different guidelines for length and required sections.

Before you begin writing, be sure to talk with your supervisor to gain a clear understanding of their specific expectations, and continually check in with them throughout the writing process.

• Organizing your Research Proposal - Template This 6-page fillable pdf handout provides writers with a template to begin outlining sections of their own research proposal.

This template can be used in conjunction with the sections below.

What are some keywords for your research?

• Should give a clear indication of your proposed research approach or key question
• Should be concise and descriptive

Writing Tip: When constructing your title, think about the search terms you would use to find this research online.

Important: Write this section last, after you have completed drafting the proposal. Or if you are required to draft a preliminary abstract, then remember to rewrite the abstract after you have completed drafting the entire proposal because some information may need to be revised.

The abstract should provide a brief overview of the entire proposal. Briefly state the research question (or hypothesis, thesis statement, aim), the problem and rationale, the proposed methods, and the proposed analyses or expected results.

The purpose of the introduction is to communicate the information that is essential for the reader to understand the overall area of concern. Be explicit. Outline why this research must be conducted and try to do so without unnecessary jargon or overwhelming detail.

Start with a short statement that establishes the overall area of concern. Avoid too much detail. Get to the point. Communicate only information essential for the reader’s comprehension. Avoid unnecessary technical language and jargon. Answer the question, "What is this study about?"

Questions to consider:

• What is your topic area, and what is the problem within that topic?
• What does the relevant literature say about the problem? – Be selective and focused.
• What are the critical, theoretical, or methodological issues directly related to the problem to be investigated?
• What are the reasons for undertaking the research? – This is the answer to the "so what?" question.

The following sections - listed as part of the introduction - are intended as a guide for drafting a research proposal. Most introductions include these following components. However, be sure to clarify with your advisor or carefully review the grant guidelines to be sure to comply with the proposal genre expectations of your specific discipline.

Broad topic and focus of study

• Briefly describe the broad topic of your research area, and then clearly explain the narrowed focus of your specific study.

Importance of topic/field of study

• Position your project in a current important research area.
• Address the “So what?” question directly, and as soon as possible.
• Provide context for the reader to understand the problem you are about to pose or research question you are asking.

Problem within field of study

• Identify the problem that you are investigating in your study.

Gap(s) in knowledge

• Identify something missing from the literature.
• What is unknown in this specific research area? This is what your study will explore and where you will attempt to provide new insights.
• Is there a reason this gap exists? Where does the current literature agree and where does it disagree? How you fill this gap (at least partially) with your research?
• Convince your reader that the problem has been appropriately defined and that the study is worth doing. Be explicit and detailed.
• Develop your argument logically and provide evidence.
• Explain why you are the person to do this project. Summarize any previous work or studies you may have undertaken in this field or research area.

Research question or hypothesis

• Foreshadow outcomes of your research. What is the question you are hoping to answer? What are the specific hypotheses to be tested and/or issues to be explored?
• Use questions when research is exploratory.
• Use declarative statements when existing knowledge enables predictions.
• List any secondary or subsidiary questions if applicable.

Purpose statement

• State the purpose of your research. Be succinct and simple.
• Why do you want to do this study?
• What is your research trying to find out?

Goals for proposed research

• Write a brief, broad statement of what you hope to accomplish and why (e.g., Improve something… Understand something… ). Are there specific measurable outcomes that you will accomplish in your study? 
• You will have a chance to go into greater detail in the research question and methodology sections.

Background or context (or literature review)

• What does the existing research on this topic say?
• Briefly state what you already know and introduce literature most relevant to your research.
• Indicate main research findings, methodologies, and interpretations from previous related studies.
• Discuss how your question or hypothesis relates to what is already known.
• Position your research within the field’s developing body of knowledge.
• Explain and support your choice of methodology or theoretical framework.

The research question is the question you are hoping to answer in your research project. It is important to know how you should write your research question into your proposal. Some proposals include

• a research question, written as a question
• or, a hypothesis as a potential response to the research question
• or, a thesis statement as an argument that answers the research question
• or, aims and objects as accomplishment or operational statements

Foreshadow the outcomes of your research. Are you trying to improve something? Understand something? Advocate for a social responsibility?

Research question

What is the question you are hoping to answer?

Subsidiary questions (if applicable)

• Does your major research question hinge on a few smaller questions? Which will you address first?

Your hypothesis should provide one (of many) possible answers to your research question.

• What are the specific hypotheses to be tested and/or issues to be explored?
• What results do you anticipate for this experiment?

Usually a hypothesis is written to show the relationship between the independent and dependent variables. Your hypothesis must be

• An expected relationship between variables
• Falsifiable
• Consistent with the existing body of knowledge

Thesis statement

Your thesis statement is a clear, concise statement of what you are arguing and why it is important. For more support on writing thesis statements, check out these following resources:

• 5 Types of Thesis Statements - Learn about five different types of thesis statements to help you choose the best type for your research.
• Templates for Writing Thesis Statements - This template provides a two-step guide for writing thesis statements.
• 5 Questions to Strengthen Your Thesis Statement - Follow these five steps to strengthen your thesis statements.

Aims and objectives

Aims are typically broader statements of what you are trying to accomplish and may or may not be measurable. Objectives are operational statements indicating specifically how you will accomplish the aims of your project.

• What are you trying to accomplish?
• How are you going to address the research question?

Be specific and make sure your aims or objectives are realistic. You want to convey that it is feasible to answer this question with the objectives you have proposed.

Make it clear that you know what you are going to do, how you are going to do it, and why it will work by relating your methodology to previous research. If there isn’t much literature on the topic, you can relate your methodology to your own preliminary research or point out how your methodology tackles something that may have been overlooked in previous studies.

Explain how you will conduct this research. Specify scope and parameters (e.g., geographic locations, demographics). Limit your inclusion of literature to only essential articles and studies.

• How will these methods produce an answer to your research question?
• How do the methods relate to the introduction and literature review?
• Have you done any previous work (or read any literature) that would inform your choices about methodology?
• Are your methods feasible and adequate? How do you know?
• What obstacles might you encounter in conducting the research, and how will you overcome them?

This section should include the following components that are relevant to your study and research methodologies:

Object(s) of study / participants / population

Provide detail about your objects of study (e.g., literary texts, swine, government policies, children, health care systems).

• Who/what are they?
• How will you find, select, or collect them?
• How feasible is it to find/select them?
• Are there any limitations to sample/data collection?
• Do you need to travel to collect samples or visit archives, etc.?
• Do you need to obtain Research Ethics Board (REB) approval to include human participants?

Theoretical frame or critical methodology

• Explain the theories or disciplinary methodologies that your research draws from or builds upon.

Materials and apparatus

• What are your survey or interview methods? (You may include a copy of questionnaires, etc.)
• Do you require any special equipment?
• How do you plan to purchase or construct or obtain this equipment?

Procedure and design

What exactly will you do? Include variables selected or manipulated, randomization, controls, the definition of coding categories, etc.

• Is it a questionnaire? Laboratory experiment? Series of interviews? Systematic review? Interpretative analysis?
• How will subjects be assigned to experimental conditions?
• What precautions will be used to control possible confounding variables?
• How long do you expect to spend on each step, and do you have a backup plan?

Data analysis and statistical procedures

• How do you plan to statistically analyze your data?
• What analyses will you conduct?
• How will the analyses contribute to the objectives?

What are the expected outcomes from your methods? Describe your expected results in relation to your hypothesis. Support these results using existing literature.

• What results would prove or disprove your hypotheses and validate your methodology, and why?
• What obstacles might you encounter in obtaining your results, and how will you deal with those obstacles?
• How will you analyze and interpret your results?

This section may be the most important part of your proposal. Make sure to emphasize how this research is significant to the related field, and how it will impact the broader community, now and in the future.

Convince your reader why this project should be funded above the other potential projects. Why is this research useful and relevant? Why is it useful to others? Answer the question “so what?”

Specific contributions

• How will your anticipated results specifically contribute to fulfilling the aims, objectives, or goals of your research?
• Will these be direct or indirect contributions? – theoretical or applied?
• How will your research contribute to the larger topic area or research discipline?

Impact and significance

• How will your research contribute to the research field of study?
• How will your research contribute to the larger topic addressed in your introduction?
• How will this research extend other work that you have done?
• How will this contribution/significance convince the reader that this research will be useful and relevant?
• Who else might find your research useful and relevant? (e.g., other research streams, policy makers, professional fields, etc.)

Provide a list of some of the most important sources that you will need to use for the introduction and background sections, plus your literature review and theoretical framework. 

What are some of the most important sources that you will need to use for the intro/background/lit review/theoretical framework? 

• Find out what style guide you are required to follow (e.g., APA, MLA, Chicago).
• Follow the guidelines in our Cite Your Sources  Libguide to format citations and create a reference list or bibliography.

Attach this list to your proposal as a separate page unless otherwise specified.

This section should include only visuals that help illustrate the preliminary results, methods, or expected results.

• What visuals will you use to help illustrate the methods or expected results?
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• v.53(4); 2010 Aug

Research questions, hypotheses and objectives

Patricia farrugia.

* Michael G. DeGroote School of Medicine, the

Bradley A. Petrisor

† Division of Orthopaedic Surgery and the

Forough Farrokhyar

‡ Departments of Surgery and

§ Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ont

Mohit Bhandari

There is an increasing familiarity with the principles of evidence-based medicine in the surgical community. As surgeons become more aware of the hierarchy of evidence, grades of recommendations and the principles of critical appraisal, they develop an increasing familiarity with research design. Surgeons and clinicians are looking more and more to the literature and clinical trials to guide their practice; as such, it is becoming a responsibility of the clinical research community to attempt to answer questions that are not only well thought out but also clinically relevant. The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently what data will be collected and analyzed. 1

Objectives of this article

In this article, we discuss important considerations in the development of a research question and hypothesis and in defining objectives for research. By the end of this article, the reader will be able to appreciate the significance of constructing a good research question and developing hypotheses and research objectives for the successful design of a research study. The following article is divided into 3 sections: research question, research hypothesis and research objectives.

Research question

Interest in a particular topic usually begins the research process, but it is the familiarity with the subject that helps define an appropriate research question for a study. 1 Questions then arise out of a perceived knowledge deficit within a subject area or field of study. 2 Indeed, Haynes suggests that it is important to know “where the boundary between current knowledge and ignorance lies.” 1 The challenge in developing an appropriate research question is in determining which clinical uncertainties could or should be studied and also rationalizing the need for their investigation.

Increasing one’s knowledge about the subject of interest can be accomplished in many ways. Appropriate methods include systematically searching the literature, in-depth interviews and focus groups with patients (and proxies) and interviews with experts in the field. In addition, awareness of current trends and technological advances can assist with the development of research questions. 2 It is imperative to understand what has been studied about a topic to date in order to further the knowledge that has been previously gathered on a topic. Indeed, some granting institutions (e.g., Canadian Institute for Health Research) encourage applicants to conduct a systematic review of the available evidence if a recent review does not already exist and preferably a pilot or feasibility study before applying for a grant for a full trial.

In-depth knowledge about a subject may generate a number of questions. It then becomes necessary to ask whether these questions can be answered through one study or if more than one study needed. 1 Additional research questions can be developed, but several basic principles should be taken into consideration. 1 All questions, primary and secondary, should be developed at the beginning and planning stages of a study. Any additional questions should never compromise the primary question because it is the primary research question that forms the basis of the hypothesis and study objectives. It must be kept in mind that within the scope of one study, the presence of a number of research questions will affect and potentially increase the complexity of both the study design and subsequent statistical analyses, not to mention the actual feasibility of answering every question. 1 A sensible strategy is to establish a single primary research question around which to focus the study plan. 3 In a study, the primary research question should be clearly stated at the end of the introduction of the grant proposal, and it usually specifies the population to be studied, the intervention to be implemented and other circumstantial factors. 4

Hulley and colleagues 2 have suggested the use of the FINER criteria in the development of a good research question ( Box 1 ). The FINER criteria highlight useful points that may increase the chances of developing a successful research project. A good research question should specify the population of interest, be of interest to the scientific community and potentially to the public, have clinical relevance and further current knowledge in the field (and of course be compliant with the standards of ethical boards and national research standards).

FINER criteria for a good research question

Adapted with permission from Wolters Kluwer Health. 2

Whereas the FINER criteria outline the important aspects of the question in general, a useful format to use in the development of a specific research question is the PICO format — consider the population (P) of interest, the intervention (I) being studied, the comparison (C) group (or to what is the intervention being compared) and the outcome of interest (O). 3 , 5 , 6 Often timing (T) is added to PICO ( Box 2 ) — that is, “Over what time frame will the study take place?” 1 The PICOT approach helps generate a question that aids in constructing the framework of the study and subsequently in protocol development by alluding to the inclusion and exclusion criteria and identifying the groups of patients to be included. Knowing the specific population of interest, intervention (and comparator) and outcome of interest may also help the researcher identify an appropriate outcome measurement tool. 7 The more defined the population of interest, and thus the more stringent the inclusion and exclusion criteria, the greater the effect on the interpretation and subsequent applicability and generalizability of the research findings. 1 , 2 A restricted study population (and exclusion criteria) may limit bias and increase the internal validity of the study; however, this approach will limit external validity of the study and, thus, the generalizability of the findings to the practical clinical setting. Conversely, a broadly defined study population and inclusion criteria may be representative of practical clinical practice but may increase bias and reduce the internal validity of the study.

PICOT criteria 1

A poorly devised research question may affect the choice of study design, potentially lead to futile situations and, thus, hamper the chance of determining anything of clinical significance, which will then affect the potential for publication. Without devoting appropriate resources to developing the research question, the quality of the study and subsequent results may be compromised. During the initial stages of any research study, it is therefore imperative to formulate a research question that is both clinically relevant and answerable.

Research hypothesis

The primary research question should be driven by the hypothesis rather than the data. 1 , 2 That is, the research question and hypothesis should be developed before the start of the study. This sounds intuitive; however, if we take, for example, a database of information, it is potentially possible to perform multiple statistical comparisons of groups within the database to find a statistically significant association. This could then lead one to work backward from the data and develop the “question.” This is counterintuitive to the process because the question is asked specifically to then find the answer, thus collecting data along the way (i.e., in a prospective manner). Multiple statistical testing of associations from data previously collected could potentially lead to spuriously positive findings of association through chance alone. 2 Therefore, a good hypothesis must be based on a good research question at the start of a trial and, indeed, drive data collection for the study.

The research or clinical hypothesis is developed from the research question and then the main elements of the study — sampling strategy, intervention (if applicable), comparison and outcome variables — are summarized in a form that establishes the basis for testing, statistical and ultimately clinical significance. 3 For example, in a research study comparing computer-assisted acetabular component insertion versus freehand acetabular component placement in patients in need of total hip arthroplasty, the experimental group would be computer-assisted insertion and the control/conventional group would be free-hand placement. The investigative team would first state a research hypothesis. This could be expressed as a single outcome (e.g., computer-assisted acetabular component placement leads to improved functional outcome) or potentially as a complex/composite outcome; that is, more than one outcome (e.g., computer-assisted acetabular component placement leads to both improved radiographic cup placement and improved functional outcome).

However, when formally testing statistical significance, the hypothesis should be stated as a “null” hypothesis. 2 The purpose of hypothesis testing is to make an inference about the population of interest on the basis of a random sample taken from that population. The null hypothesis for the preceding research hypothesis then would be that there is no difference in mean functional outcome between the computer-assisted insertion and free-hand placement techniques. After forming the null hypothesis, the researchers would form an alternate hypothesis stating the nature of the difference, if it should appear. The alternate hypothesis would be that there is a difference in mean functional outcome between these techniques. At the end of the study, the null hypothesis is then tested statistically. If the findings of the study are not statistically significant (i.e., there is no difference in functional outcome between the groups in a statistical sense), we cannot reject the null hypothesis, whereas if the findings were significant, we can reject the null hypothesis and accept the alternate hypothesis (i.e., there is a difference in mean functional outcome between the study groups), errors in testing notwithstanding. In other words, hypothesis testing confirms or refutes the statement that the observed findings did not occur by chance alone but rather occurred because there was a true difference in outcomes between these surgical procedures. The concept of statistical hypothesis testing is complex, and the details are beyond the scope of this article.

Another important concept inherent in hypothesis testing is whether the hypotheses will be 1-sided or 2-sided. A 2-sided hypothesis states that there is a difference between the experimental group and the control group, but it does not specify in advance the expected direction of the difference. For example, we asked whether there is there an improvement in outcomes with computer-assisted surgery or whether the outcomes worse with computer-assisted surgery. We presented a 2-sided test in the above example because we did not specify the direction of the difference. A 1-sided hypothesis states a specific direction (e.g., there is an improvement in outcomes with computer-assisted surgery). A 2-sided hypothesis should be used unless there is a good justification for using a 1-sided hypothesis. As Bland and Atlman 8 stated, “One-sided hypothesis testing should never be used as a device to make a conventionally nonsignificant difference significant.”

The research hypothesis should be stated at the beginning of the study to guide the objectives for research. Whereas the investigators may state the hypothesis as being 1-sided (there is an improvement with treatment), the study and investigators must adhere to the concept of clinical equipoise. According to this principle, a clinical (or surgical) trial is ethical only if the expert community is uncertain about the relative therapeutic merits of the experimental and control groups being evaluated. 9 It means there must exist an honest and professional disagreement among expert clinicians about the preferred treatment. 9

Designing a research hypothesis is supported by a good research question and will influence the type of research design for the study. Acting on the principles of appropriate hypothesis development, the study can then confidently proceed to the development of the research objective.

Research objective

The primary objective should be coupled with the hypothesis of the study. Study objectives define the specific aims of the study and should be clearly stated in the introduction of the research protocol. 7 From our previous example and using the investigative hypothesis that there is a difference in functional outcomes between computer-assisted acetabular component placement and free-hand placement, the primary objective can be stated as follows: this study will compare the functional outcomes of computer-assisted acetabular component insertion versus free-hand placement in patients undergoing total hip arthroplasty. Note that the study objective is an active statement about how the study is going to answer the specific research question. Objectives can (and often do) state exactly which outcome measures are going to be used within their statements. They are important because they not only help guide the development of the protocol and design of study but also play a role in sample size calculations and determining the power of the study. 7 These concepts will be discussed in other articles in this series.

From the surgeon’s point of view, it is important for the study objectives to be focused on outcomes that are important to patients and clinically relevant. For example, the most methodologically sound randomized controlled trial comparing 2 techniques of distal radial fixation would have little or no clinical impact if the primary objective was to determine the effect of treatment A as compared to treatment B on intraoperative fluoroscopy time. However, if the objective was to determine the effect of treatment A as compared to treatment B on patient functional outcome at 1 year, this would have a much more significant impact on clinical decision-making. Second, more meaningful surgeon–patient discussions could ensue, incorporating patient values and preferences with the results from this study. 6 , 7 It is the precise objective and what the investigator is trying to measure that is of clinical relevance in the practical setting.

The following is an example from the literature about the relation between the research question, hypothesis and study objectives:

Study: Warden SJ, Metcalf BR, Kiss ZS, et al. Low-intensity pulsed ultrasound for chronic patellar tendinopathy: a randomized, double-blind, placebo-controlled trial. Rheumatology 2008;47:467–71.

Research question: How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?

Research hypothesis: Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).

Objective: To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

The development of the research question is the most important aspect of a research project. A research project can fail if the objectives and hypothesis are poorly focused and underdeveloped. Useful tips for surgical researchers are provided in Box 3 . Designing and developing an appropriate and relevant research question, hypothesis and objectives can be a difficult task. The critical appraisal of the research question used in a study is vital to the application of the findings to clinical practice. Focusing resources, time and dedication to these 3 very important tasks will help to guide a successful research project, influence interpretation of the results and affect future publication efforts.

Tips for developing research questions, hypotheses and objectives for research studies

• Perform a systematic literature review (if one has not been done) to increase knowledge and familiarity with the topic and to assist with research development.
• Learn about current trends and technological advances on the topic.
• Seek careful input from experts, mentors, colleagues and collaborators to refine your research question as this will aid in developing the research question and guide the research study.
• Use the FINER criteria in the development of the research question.
• Ensure that the research question follows PICOT format.
• Develop a research hypothesis from the research question.
• Develop clear and well-defined primary and secondary (if needed) objectives.
• Ensure that the research question and objectives are answerable, feasible and clinically relevant.

FINER = feasible, interesting, novel, ethical, relevant; PICOT = population (patients), intervention (for intervention studies only), comparison group, outcome of interest, time.

Competing interests: No funding was received in preparation of this paper. Dr. Bhandari was funded, in part, by a Canada Research Chair, McMaster University.

Journal of Materials Chemistry A

Copper- and manganese-based layered hybrid organic–inorganic compounds with polymorphic transitions as energy storage materials †.

* Corresponding authors

a Department of Materials Science and Physical Chemistry, Section of Materials Science and Engineering, Faculty of Chemistry, Universitat de Barcelona, C/ Martí i Franquès 1-11, Barcelona, Spain E-mail: [email protected]

b X-ray Diffraction Unit, Scientific and Technological Centers, University of Barcelona, Lluís Solé i Sabarís 1-3, Barcelona, Spain

c Department of Inorganic and Organic Chemistry, Section of Organic Chemistry, Faculty of Chemistry, Universitat de Barcelona, C/ Martí i Franquès 1-11, 08028 Barcelona, Spain

Solid–solid phase change materials (ss-PCM) have emerged as a promising alternative to traditional methods of thermal regulation, such as solid–liquid transformations. Due to their wide operational temperature range and competitive performance, ss-PCM materials are increasingly being explored for their potential in cooling electronic devices. Here, we explore the potential of layered hybrid organic–inorganic perovskites (LHOIPs) as thermal energy storage materials for passive cooling applications. Two formulations, bis(dodecylammonium) tetrachlorocuprate( II ) (CuC 12 ) and bis(dodecylammonium) tetrachloromanganate( II ) (MnC 12 ) were synthesised and comprehensively characterised. The analyses revealed that these materials present a two-dimensional structure with a triclinic conformation at 100 K. Notably, both materials exhibited a polymorphic transformation with low thermal hysteresis (1.3–2.5 K). These findings indicate that these materials hold significant potential as thermoregulator materials in cooling electronics. Furthermore, both CuC 12 and MnC 12 demonstrated good thermal stability compared to other types of ss-PCM. Overall, the findings of this study suggest that LHOIPs, particularly CuC 12 and MnC 12 , are promising candidates for further exploration as thermal energy storage materials in electronic cooling applications.

Supplementary files

• Supplementary information PDF (498K)
• Crystal structure data CIF (2773K)

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Copper- and manganese-based layered hybrid organic–inorganic compounds with polymorphic transitions as energy storage materials

R. Salgado-Pizarro, C. Puigjaner, J. García, A. I. Fernández and C. Barreneche, J. Mater. Chem. A , 2024, Advance Article , DOI: 10.1039/D4TA01060D

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