5 Characteristics of a Good Hypothesis: A Guide for Researchers
- by Brian Thomas
- October 4, 2024
Are you a curious soul, always seeking answers to the whys and hows of the world? As a researcher, formulating a hypothesis is a crucial first step towards unraveling the mysteries of your study. A well-crafted hypothesis not only guides your research but also lays the foundation for drawing valid conclusions. But what exactly makes a hypothesis a good one? In this blog post, we will explore the five key characteristics of a good hypothesis that every researcher should know.
Here, we will delve into the world of hypotheses, covering everything from their types in research to understanding if they can be proven true. Whether you’re a seasoned researcher or just starting out, this blog post will provide valuable insights on how to craft a sound hypothesis for your study. So let’s dive in and uncover the secrets to formulating a hypothesis that stands strong amidst the scientific rigor!
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5 Characteristics of a Good Hypothesis
Clear and specific.
A good hypothesis is like a GPS that guides you to the right destination. It needs to be clear and specific so that you know exactly what you’re testing. Avoid vague statements or general ideas. Instead, focus on crafting a hypothesis that clearly states the relationship between variables and the expected outcome. Clarity is key, my friend!
Testable and Falsifiable
A hypothesis might sound great in theory, but if you can’t test it or prove it wrong, then it’s like chasing unicorns. A good hypothesis should be testable and falsifiable – meaning there should be a way to gather evidence to support or refute it. Don’t be afraid to challenge your hypothesis and put it to the test. Only when it can be proven false can it truly be considered a good hypothesis.
Based on Existing Knowledge
Imagine trying to build a Lego tower without any Lego bricks. That’s what it’s like to come up with a hypothesis that has no basis in existing knowledge. A good hypothesis is grounded in previous research, theories, or observations. It shows that you’ve done your homework and understand the current state of knowledge in your field. So, put on your research hat and gather those building blocks for a solid hypothesis!
Specific Predictions
No, we’re not talking about crystal ball predictions or psychic abilities here. A good hypothesis includes specific predictions about what you expect to happen. It’s like making an educated guess based on your understanding of the variables involved. These predictions help guide your research and give you something concrete to look for. So, put on those prediction goggles, my friend, and let’s get specific!
Relevant to the Research Question
A hypothesis is a road sign that points you in the right direction. But if it’s not relevant to your research question, then you might end up in a never-ending detour. A good hypothesis aligns with your research question and addresses the specific problem or phenomenon you’re investigating. Keep your focus on the main topic and avoid getting sidetracked by shiny distractions. Stay relevant, my friend, and you’ll find the answers you seek!
And there you have it: the five characteristics of a good hypothesis. Remember, a good hypothesis is clear, testable, based on existing knowledge, makes specific predictions, and is relevant to your research question. So go forth, my friend, and hypothesize your way to scientific discovery!
FAQs: Characteristics of a Good Hypothesis
In the realm of scientific research, a hypothesis plays a crucial role in formulating and testing ideas. A good hypothesis serves as the foundation for an experiment or study, guiding the researcher towards meaningful results. In this FAQ-style subsection, we’ll explore the characteristics of a good hypothesis, their types, formulation, and more. So let’s dive in and unravel the mysteries of hypothesis-making!
What Are Two Important Characteristics of a Good Hypothesis
A good hypothesis possesses two important characteristics:
Testability : A hypothesis must be testable to determine its validity. It should be formulated in a way that allows researchers to design and conduct experiments or gather data for analysis. For example, if we hypothesize that “drinking herbal tea reduces stress,” we can easily test it by conducting a study with a control group and a group drinking herbal tea.
Falsifiability : Falsifiability refers to the potential for a hypothesis to be proven wrong. A good hypothesis should make specific predictions that can be refuted or supported by evidence. This characteristic ensures that hypotheses are based on empirical observations rather than personal opinions. For instance, the hypothesis “all swans are white” can be falsified by discovering a single black swan.
What Are the Types of Hypothesis in Research
In research, there are three main types of hypotheses:
Null Hypothesis (H0) : The null hypothesis is a statement of no effect or relationship. It assumes that there is no significant difference between variables or no effect of a treatment. Researchers aim to reject the null hypothesis in favor of an alternative hypothesis.
Alternative Hypothesis (HA or H1) : The alternative hypothesis is the opposite of the null hypothesis. It asserts that there is a significant difference between variables or an effect of a treatment. Researchers seek evidence to support the alternative hypothesis.
Directional Hypothesis : A directional hypothesis predicts the specific direction of the relationship or difference between variables. For example, “increasing exercise duration will lead to greater weight loss.”
Can a Hypothesis Be Proven True
In scientific research, hypotheses are not proven true; they are supported or rejected based on empirical evidence . Even if a hypothesis is supported by multiple studies, new evidence could arise that contradicts it. Scientific knowledge is always subject to revision and refinement. Therefore, the goal is to gather enough evidence to either support or reject a hypothesis, rather than proving it absolutely true.
What Are the Six Parts of a Hypothesis
A hypothesis typically consists of six essential parts:
Research Question : A clear and concise question that the hypothesis seeks to answer.
Variables : Identification of the independent (manipulated) and dependent (measured) variables involved in the hypothesis.
Population : The specific group or individuals the hypothesis is concerned with.
Relationship or Comparison : The expected relationship or difference between variables, often indicated by directional terms like “more,” “less,” “higher,” or “lower.”
Predictability : A statement of the predicted outcome or result based on the relationship between variables.
Testability : The ability to design an experiment or gather data to support or reject the hypothesis.
How Do You Start a Hypothesis Sentence
When starting a hypothesis sentence, it is essential to use clear and concise language to express your ideas. A common approach is to use the phrase “If…then…” to establish the conditional relationship between variables. For example:
- If [independent variable], then [dependent variable] because [explanation of expected relationship].
This structure allows for a straightforward and logical formulation of the hypothesis.
What Are Examples of Hypotheses
Here are a few examples of well-formulated hypotheses:
If exposure to sunlight increases, then plants will grow taller because sunlight is necessary for photosynthesis.
If students receive praise for good grades, then their motivation to excel will increase because they seek recognition and approval.
If the dose of a painkiller is increased, then the relief from pain will last longer because a higher dosage has a prolonged effect.
What Are the Five Key Elements to a Good Hypothesis
A good hypothesis should include the following five key elements:
Clarity : The hypothesis should be clear and specific, leaving no room for interpretation.
Testability : It should be possible to test the hypothesis through experimentation or data collection.
Relevance : The hypothesis should be directly tied to the research question or problem being investigated.
Specificity : It must clearly state the relationship or difference between variables being studied.
Falsifiability : The hypothesis should make predictions that can be refuted or supported by empirical evidence.
What Makes a Good Hypothesis in a Research Paper
In a research paper, a good hypothesis should have the following characteristics:
Relevance : It must directly relate to the research topic and address the objectives of the study.
Clarity : The hypothesis should be concise and precisely worded to avoid confusion.
Unambiguous : It must leave no room for multiple interpretations or ambiguity.
Logic : The hypothesis should be based on rational and logical reasoning, considering existing theories and observations.
Empirical Support : Ideally, the hypothesis should be supported by prior empirical evidence or strong theoretical justifications.
Is a Hypothesis Always a Question
No, a hypothesis is not always in the form of a question. While some hypotheses can take the form of a question, others may be statements asserting a relationship or difference between variables. The form of a hypothesis depends on the research question being addressed and the researcher’s preferred style of expression.
What Are the Three Things Needed for a Good Hypothesis
For a hypothesis to be considered good, it must fulfill the following three criteria:
Testability : The hypothesis should be formulated in a way that allows for empirical testing through experimentation or data collection.
Falsifiability : It must make specific predictions that can be potentially refuted or supported by evidence.
Relevance : The hypothesis should directly address the research question or problem being investigated.
What Are the Four Components to a Good Hypothesis
A good hypothesis typically consists of four components:
Independent Variable : The variable being manipulated or controlled by the researcher.
Dependent Variable : The variable being measured or observed to determine the effect of the independent variable.
Directionality : The predicted relationship or difference between the independent and dependent variables.
Population : The specific group or individuals to which the hypothesis applies.
How Do You Formulate a Hypothesis
To formulate a hypothesis, follow these steps:
Identify the Research Topic : Clearly define the area or phenomenon you want to study.
Conduct Background Research : Review existing literature and research to gain knowledge about the topic.
Formulate a Research Question : Ask a clear and focused question that you want to answer through your hypothesis.
State the Null and Alternative Hypotheses : Develop a null hypothesis to assume no effect or relationship, and an alternative hypothesis to propose a significant effect or relationship.
Decide on Variables and Relationships : Determine the independent and dependent variables and the predicted relationship between them.
Refine and Test : Refine your hypothesis, ensuring it is clear, testable, and falsifiable. Then, design experiments or gather data to support or reject it.
What Is a Characteristic of a Hypothesis MCQ
Multiple-choice questions (MCQ) regarding the characteristics of a hypothesis often assess knowledge on the testability and falsifiability of hypotheses. They may ask about the criteria that distinguish a good hypothesis from a poor one or the importance of making specific predictions. Remember to choose answers that emphasize the empirical and testable nature of hypotheses.
What Five Criteria Must Be Satisfied for a Hypothesis to Be Scientific
For a hypothesis to be considered scientific, it must satisfy the following five criteria:
Testability : The hypothesis must be formulated in a way that allows it to be tested through experimentation or data collection.
Falsifiability : It should make specific predictions that can be potentially refuted or supported by empirical evidence.
Empirical Basis : The hypothesis should be based on empirical observations or existing theories and knowledge.
Relevance : It must directly address the research question or problem being investigated.
Objective : A scientific hypothesis should be free from personal biases or subjective opinions, focusing on objective observations and analysis.
What Are the Steps of Theory Development in Scientific Methods
In scientific methods, theory development typically involves the following steps:
Observation : Identifying a phenomenon or pattern worthy of investigation through observation or empirical data.
Formulation of a Hypothesis : Constructing a hypothesis that explains the observed phenomena or predicts a relationship between variables.
Data Collection : Gathering relevant data through experiments, surveys, observations, or other research methods.
Analysis : Analyzing the collected data to evaluate the hypothesis’s predictions and determine their validity.
Revision and Refinement : Based on the analysis, refining the hypothesis, modifying the theory, or formulating new hypotheses for further investigation.
Which of the Following Makes a Good Hypothesis
A good hypothesis is characterized by:
Testability : The ability to form experiments or gather data to support or refute the hypothesis.
Falsifiability : The potential for the hypothesis’s predictions to be proven wrong based on empirical evidence.
Clarity : A clear and concise statement or question that leaves no room for ambiguity.
Relevancy : Directly addressing the research question or problem at hand.
Remember, it is important to select the option that encompasses all these characteristics.
What Are the Characteristics of a Good Hypothesis
A good hypothesis possesses several characteristics, such as:
Testability : It should allow for empirical testing through experiments or data collection.
Falsifiability : The hypothesis should make specific predictions that can be potentially refuted or supported by evidence.
Clarity : It must be clearly and precisely formulated, leaving no room for ambiguity or multiple interpretations.
Relevance : The hypothesis should directly relate to the research question or problem being investigated.
What Is the Five-Step p-value Approach to Hypothesis Testing
The five-step p-value approach is a commonly used framework for hypothesis testing:
Step 1: Formulating the Hypotheses : The null hypothesis (H0) assumes no effect or relationship, while the alternative hypothesis (HA) proposes a significant effect or relationship.
Step 2: Setting the Significance Level : Decide on the level of significance (α), which represents the probability of rejecting the null hypothesis when it is true. The commonly used level is 0.05 (5%).
Step 3: Collecting Data and Performing the Test : Acquire and analyze the data, calculating the test statistic and the corresponding p-value.
Step 4: Comparing the p-value with the Significance Level : If the p-value is less than the significance level (α), reject the null hypothesis. Otherwise, fail to reject the null hypothesis.
Step 5: Drawing Conclusions : Based on the comparison in Step 4, interpret the results and draw conclusions about the hypothesis.
What Are the Stages of Hypothesis
The stages of hypothesis generally include:
Observation : Identifying a pattern, phenomenon, or research question that warrants investigation.
Formulation : Developing a hypothesis that explains or predicts the relationship or difference between variables.
Testing : Collecting data, designing experiments, or conducting studies to gather evidence supporting or refuting the hypothesis.
Analysis : Assessing the collected data to determine whether the results support or reject the hypothesis.
Conclusion : Drawing conclusions based on the analysis and making further iterations, refinements, or new hypotheses for future research.
What Is a Characteristic of a Good Hypothesis
A characteristic of a good hypothesis is its ability to make specific predictions about the relationship or difference between variables. Good hypotheses avoid vague statements and clearly articulate the expected outcomes. By doing so, researchers can design experiments or gather data that directly test the predictions, leading to meaningful results.
How Do You Write a Good Hypothesis Example
To write a good hypothesis example, follow these guidelines:
If possible, use the “If…then…” format to express a conditional relationship between variables.
Be clear and concise in stating the variables involved, the predicted relationship, and the expected outcome.
Ensure the hypothesis is testable, meaning it can be evaluated through experiments or data collection.
For instance, consider the following example:
If students study for longer periods of time, then their test scores will improve because increased study time allows for better retention of information and increased proficiency.
What Is the Difference Between Hypothesis and Hypotheses
The main difference between a hypothesis and hypotheses lies in their grammatical number. A hypothesis refers to a single statement or proposition that is formulated to explain or predict the relationship between variables. On the other hand, hypotheses is the plural form of the term hypothesis, commonly used when multiple statements or propositions are proposed and tested simultaneously.
What Is a Good Hypothesis Statement
A good hypothesis statement exhibits the following qualities:
Clarity : It is written in clear and concise language, leaving no room for confusion or ambiguity.
Testability : The hypothesis should be formulated in a way that enables testing through experiments or data collection.
Specificity : It must clearly state the predicted relationship or difference between variables.
By adhering to these criteria, a good hypothesis statement guides research efforts effectively.
What Is Not a Characteristic of a Good Hypothesis
A characteristic that does not align with a good hypothesis is subjectivity . A hypothesis should be objective, based on empirical observations or existing theories, and free from personal bias. While personal interpretations and opinions can inspire the formulation of a hypothesis, it must ultimately rely on objective observations and be open to empirical testing.
By now, you’ve gained insights into the characteristics of a good hypothesis, including testability, falsifiability, clarity,
- characteristics
- falsifiable
- good hypothesis
- hypothesis testing
- null hypothesis
- observations
- scientific rigor
Brian Thomas
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How to Write a Great Hypothesis
Hypothesis Definition, Format, Examples, and Tips
Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk, "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.
Verywell / Alex Dos Diaz
- The Scientific Method
Hypothesis Format
Falsifiability of a hypothesis.
- Operationalization
Hypothesis Types
Hypotheses examples.
- Collecting Data
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.
Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."
At a Glance
A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.
The Hypothesis in the Scientific Method
In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:
- Forming a question
- Performing background research
- Creating a hypothesis
- Designing an experiment
- Collecting data
- Analyzing the results
- Drawing conclusions
- Communicating the results
The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.
Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.
In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.
Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.
In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.
In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."
In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."
Elements of a Good Hypothesis
So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:
- Is your hypothesis based on your research on a topic?
- Can your hypothesis be tested?
- Does your hypothesis include independent and dependent variables?
Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.
How to Formulate a Good Hypothesis
To form a hypothesis, you should take these steps:
- Collect as many observations about a topic or problem as you can.
- Evaluate these observations and look for possible causes of the problem.
- Create a list of possible explanations that you might want to explore.
- After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.
In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.
Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.
One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.
The Importance of Operational Definitions
A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.
Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.
For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.
These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.
Replicability
One of the basic principles of any type of scientific research is that the results must be replicable.
Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.
Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.
To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.
Hypothesis Checklist
- Does your hypothesis focus on something that you can actually test?
- Does your hypothesis include both an independent and dependent variable?
- Can you manipulate the variables?
- Can your hypothesis be tested without violating ethical standards?
The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:
- Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
- Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
- Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
- Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
- Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
- Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.
A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .
The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."
A few examples of simple hypotheses:
- "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
- "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
- "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
- "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."
Examples of a complex hypothesis include:
- "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
- "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."
Examples of a null hypothesis include:
- "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
- "There is no difference in scores on a memory recall task between children and adults."
- "There is no difference in aggression levels between children who play first-person shooter games and those who do not."
Examples of an alternative hypothesis:
- "People who take St. John's wort supplements will have less anxiety than those who do not."
- "Adults will perform better on a memory task than children."
- "Children who play first-person shooter games will show higher levels of aggression than children who do not."
Collecting Data on Your Hypothesis
Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.
Descriptive Research Methods
Descriptive research such as case studies , naturalistic observations , and surveys are often used when conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.
Once a researcher has collected data using descriptive methods, a correlational study can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.
Experimental Research Methods
Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).
Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.
The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.
Thompson WH, Skau S. On the scope of scientific hypotheses . R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607
Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:]. Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z
Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004
Nosek BA, Errington TM. What is replication ? PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691
Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18
Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.
By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
How to Write a Hypothesis? Types and Examples
All research studies involve the use of the scientific method, which is a mathematical and experimental technique used to conduct experiments by developing and testing a hypothesis or a prediction about an outcome. Simply put, a hypothesis is a suggested solution to a problem. It includes elements that are expressed in terms of relationships with each other to explain a condition or an assumption that hasn’t been verified using facts. 1 The typical steps in a scientific method include developing such a hypothesis, testing it through various methods, and then modifying it based on the outcomes of the experiments.
A research hypothesis can be defined as a specific, testable prediction about the anticipated results of a study. 2 Hypotheses help guide the research process and supplement the aim of the study. After several rounds of testing, hypotheses can help develop scientific theories. 3 Hypotheses are often written as if-then statements.
Here are two hypothesis examples:
Dandelions growing in nitrogen-rich soils for two weeks develop larger leaves than those in nitrogen-poor soils because nitrogen stimulates vegetative growth. 4
If a company offers flexible work hours, then their employees will be happier at work. 5
Table of Contents
- What is a hypothesis?
- Types of hypotheses
- Characteristics of a hypothesis
- Functions of a hypothesis
- How to write a hypothesis
- Hypothesis examples
- Frequently asked questions
What is a hypothesis?
A hypothesis expresses an expected relationship between variables in a study and is developed before conducting any research. Hypotheses are not opinions but rather are expected relationships based on facts and observations. They help support scientific research and expand existing knowledge. An incorrectly formulated hypothesis can affect the entire experiment leading to errors in the results so it’s important to know how to formulate a hypothesis and develop it carefully.
A few sources of a hypothesis include observations from prior studies, current research and experiences, competitors, scientific theories, and general conditions that can influence people. Figure 1 depicts the different steps in a research design and shows where exactly in the process a hypothesis is developed. 4
There are seven different types of hypotheses—simple, complex, directional, nondirectional, associative and causal, null, and alternative.
Types of hypotheses
The seven types of hypotheses are listed below: 5 , 6,7
- Simple : Predicts the relationship between a single dependent variable and a single independent variable.
Example: Exercising in the morning every day will increase your productivity.
- Complex : Predicts the relationship between two or more variables.
Example: Spending three hours or more on social media daily will negatively affect children’s mental health and productivity, more than that of adults.
- Directional : Specifies the expected direction to be followed and uses terms like increase, decrease, positive, negative, more, or less.
Example: The inclusion of intervention X decreases infant mortality compared to the original treatment.
- Non-directional : Does not predict the exact direction, nature, or magnitude of the relationship between two variables but rather states the existence of a relationship. This hypothesis may be used when there is no underlying theory or if findings contradict prior research.
Example: Cats and dogs differ in the amount of affection they express.
- Associative and causal : An associative hypothesis suggests an interdependency between variables, that is, how a change in one variable changes the other.
Example: There is a positive association between physical activity levels and overall health.
A causal hypothesis, on the other hand, expresses a cause-and-effect association between variables.
Example: Long-term alcohol use causes liver damage.
- Null : Claims that the original hypothesis is false by showing that there is no relationship between the variables.
Example: Sleep duration does not have any effect on productivity.
- Alternative : States the opposite of the null hypothesis, that is, a relationship exists between two variables.
Example: Sleep duration affects productivity.
Characteristics of a hypothesis
So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9
- Testable : You must be able to test the hypothesis using scientific methods to either accept or reject the prediction.
- Falsifiable : It should be possible to collect data that reject rather than support the hypothesis.
- Logical : Hypotheses shouldn’t be a random guess but rather should be based on previous theories, observations, prior research, and logical reasoning.
- Positive : The hypothesis statement about the existence of an association should be positive, that is, it should not suggest that an association does not exist. Therefore, the language used and knowing how to phrase a hypothesis is very important.
- Clear and accurate : The language used should be easily comprehensible and use correct terminology.
- Relevant : The hypothesis should be relevant and specific to the research question.
- Structure : Should include all the elements that make a good hypothesis: variables, relationship, and outcome.
Functions of a hypothesis
The following list mentions some important functions of a hypothesis: 1
- Maintains the direction and progress of the research.
- Expresses the important assumptions underlying the proposition in a single statement.
- Establishes a suitable context for researchers to begin their investigation and for readers who are referring to the final report.
- Provides an explanation for the occurrence of a specific phenomenon.
- Ensures selection of appropriate and accurate facts necessary and relevant to the research subject.
To summarize, a hypothesis provides the conceptual elements that complete the known data, conceptual relationships that systematize unordered elements, and conceptual meanings and interpretations that explain the unknown phenomena. 1
How to write a hypothesis
Listed below are the main steps explaining how to write a hypothesis. 2,4,5
- Make an observation and identify variables : Observe the subject in question and try to recognize a pattern or a relationship between the variables involved. This step provides essential background information to begin your research.
For example, if you notice that an office’s vending machine frequently runs out of a specific snack, you may predict that more people in the office choose that snack over another.
- Identify the main research question : After identifying a subject and recognizing a pattern, the next step is to ask a question that your hypothesis will answer.
For example, after observing employees’ break times at work, you could ask “why do more employees take breaks in the morning rather than in the afternoon?”
- Conduct some preliminary research to ensure originality and novelty : Your initial answer, which is your hypothesis, to the question is based on some pre-existing information about the subject. However, to ensure that your hypothesis has not been asked before or that it has been asked but rejected by other researchers you would need to gather additional information.
For example, based on your observations you might state a hypothesis that employees work more efficiently when the air conditioning in the office is set at a lower temperature. However, during your preliminary research you find that this hypothesis was proven incorrect by a prior study.
- Develop a general statement : After your preliminary research has confirmed the originality of your proposed answer, draft a general statement that includes all variables, subjects, and predicted outcome. The statement could be if/then or declarative.
- Finalize the hypothesis statement : Use the PICOT model, which clarifies how to word a hypothesis effectively, when finalizing the statement. This model lists the important components required to write a hypothesis.
P opulation: The specific group or individual who is the main subject of the research
I nterest: The main concern of the study/research question
C omparison: The main alternative group
O utcome: The expected results
T ime: Duration of the experiment
Once you’ve finalized your hypothesis statement you would need to conduct experiments to test whether the hypothesis is true or false.
Hypothesis examples
The following table provides examples of different types of hypotheses. 10 ,11
Key takeaways
Here’s a summary of all the key points discussed in this article about how to write a hypothesis.
- A hypothesis is an assumption about an association between variables made based on limited evidence, which should be tested.
- A hypothesis has four parts—the research question, independent variable, dependent variable, and the proposed relationship between the variables.
- The statement should be clear, concise, testable, logical, and falsifiable.
- There are seven types of hypotheses—simple, complex, directional, non-directional, associative and causal, null, and alternative.
- A hypothesis provides a focus and direction for the research to progress.
- A hypothesis plays an important role in the scientific method by helping to create an appropriate experimental design.
Frequently asked questions
Hypotheses and research questions have different objectives and structure. The following table lists some major differences between the two. 9
Here are a few examples to differentiate between a research question and hypothesis.
Yes, here’s a simple checklist to help you gauge the effectiveness of your hypothesis. 9 1. When writing a hypothesis statement, check if it: 2. Predicts the relationship between the stated variables and the expected outcome. 3. Uses simple and concise language and is not wordy. 4. Does not assume readers’ knowledge about the subject. 5. Has observable, falsifiable, and testable results.
As mentioned earlier in this article, a hypothesis is an assumption or prediction about an association between variables based on observations and simple evidence. These statements are usually generic. Research objectives, on the other hand, are more specific and dictated by hypotheses. The same hypothesis can be tested using different methods and the research objectives could be different in each case. For example, Louis Pasteur observed that food lasts longer at higher altitudes, reasoned that it could be because the air at higher altitudes is cleaner (with fewer or no germs), and tested the hypothesis by exposing food to air cleaned in the laboratory. 12 Thus, a hypothesis is predictive—if the reasoning is correct, X will lead to Y—and research objectives are developed to test these predictions.
Null hypothesis testing is a method to decide between two assumptions or predictions between variables (null and alternative hypotheses) in a statistical relationship in a sample. The null hypothesis, denoted as H 0 , claims that no relationship exists between variables in a population and any relationship in the sample reflects a sampling error or occurrence by chance. The alternative hypothesis, denoted as H 1 , claims that there is a relationship in the population. In every study, researchers need to decide whether the relationship in a sample occurred by chance or reflects a relationship in the population. This is done by hypothesis testing using the following steps: 13 1. Assume that the null hypothesis is true. 2. Determine how likely the sample relationship would be if the null hypothesis were true. This probability is called the p value. 3. If the sample relationship would be extremely unlikely, reject the null hypothesis and accept the alternative hypothesis. If the relationship would not be unlikely, accept the null hypothesis.
To summarize, researchers should know how to write a good hypothesis to ensure that their research progresses in the required direction. A hypothesis is a testable prediction about any behavior or relationship between variables, usually based on facts and observation, and states an expected outcome.
We hope this article has provided you with essential insight into the different types of hypotheses and their functions so that you can use them appropriately in your next research project.
References
- Dalen, DVV. The function of hypotheses in research. Proquest website. Accessed April 8, 2024. https://www.proquest.com/docview/1437933010?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals&imgSeq=1
- McLeod S. Research hypothesis in psychology: Types & examples. SimplyPsychology website. Updated December 13, 2023. Accessed April 9, 2024. https://www.simplypsychology.org/what-is-a-hypotheses.html
- Scientific method. Britannica website. Updated March 14, 2024. Accessed April 9, 2024. https://www.britannica.com/science/scientific-method
- The hypothesis in science writing. Accessed April 10, 2024. https://berks.psu.edu/sites/berks/files/campus/HypothesisHandout_Final.pdf
- How to develop a hypothesis (with elements, types, and examples). Indeed.com website. Updated February 3, 2023. Accessed April 10, 2024. https://www.indeed.com/career-advice/career-development/how-to-write-a-hypothesis
- Types of research hypotheses. Excelsior online writing lab. Accessed April 11, 2024. https://owl.excelsior.edu/research/research-hypotheses/types-of-research-hypotheses/
- What is a research hypothesis: how to write it, types, and examples. Researcher.life website. Published February 8, 2023. Accessed April 11, 2024. https://researcher.life/blog/article/how-to-write-a-research-hypothesis-definition-types-examples/
- Developing a hypothesis. Pressbooks website. Accessed April 12, 2024. https://opentext.wsu.edu/carriecuttler/chapter/developing-a-hypothesis/
- What is and how to write a good hypothesis in research. Elsevier author services website. Accessed April 12, 2024. https://scientific-publishing.webshop.elsevier.com/manuscript-preparation/what-how-write-good-hypothesis-research/
- How to write a great hypothesis. Verywellmind website. Updated March 12, 2023. Accessed April 13, 2024. https://www.verywellmind.com/what-is-a-hypothesis-2795239
- 15 Hypothesis examples. Helpfulprofessor.com Published September 8, 2023. Accessed March 14, 2024. https://helpfulprofessor.com/hypothesis-examples/
- Editage insights. What is the interconnectivity between research objectives and hypothesis? Published February 24, 2021. Accessed April 13, 2024. https://www.editage.com/insights/what-is-the-interconnectivity-between-research-objectives-and-hypothesis
- Understanding null hypothesis testing. BCCampus open publishing. Accessed April 16, 2024. https://opentextbc.ca/researchmethods/chapter/understanding-null-hypothesis-testing/#:~:text=In%20null%20hypothesis%20testing%2C%20this,said%20to%20be%20statistically%20significant
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Home » What is a Hypothesis – Types, Examples and Writing Guide
What is a Hypothesis – Types, Examples and Writing Guide
Table of Contents
In research, a hypothesis is a clear, testable statement predicting the relationship between variables or the outcome of a study. Hypotheses form the foundation of scientific inquiry, providing a direction for investigation and guiding the data collection and analysis process. Hypotheses are typically used in quantitative research but can also inform some qualitative studies by offering a preliminary assumption about the subject being explored.
A hypothesis is a specific, testable prediction or statement that suggests an expected relationship between variables in a study. It acts as a starting point, guiding researchers to examine whether their predictions hold true based on collected data. For a hypothesis to be useful, it must be clear, concise, and based on prior knowledge or theoretical frameworks.
Key Characteristics of a Hypothesis :
- Testable : Must be possible to evaluate or observe the outcome through experimentation or analysis.
- Specific : Clearly defines variables and the expected relationship or outcome.
- Predictive : States an anticipated effect or association that can be confirmed or refuted.
Example : “Increasing the amount of daily physical exercise will lead to a reduction in stress levels among college students.”
Types of Hypotheses
Hypotheses can be categorized into several types, depending on their structure, purpose, and the type of relationship they suggest. The most common types include null hypothesis , alternative hypothesis , directional hypothesis , and non-directional hypothesis .
1. Null Hypothesis (H₀)
Definition : The null hypothesis states that there is no relationship between the variables being studied or that any observed effect is due to chance. It serves as the default position, which researchers aim to test against to determine if a significant effect or association exists.
Purpose : To provide a baseline that can be statistically tested to verify if a relationship or difference exists.
Example : “There is no difference in academic performance between students who receive additional tutoring and those who do not.”
2. Alternative Hypothesis (H₁ or Hₐ)
Definition : The alternative hypothesis proposes that there is a relationship or effect between variables. This hypothesis contradicts the null hypothesis and suggests that any observed result is not due to chance.
Purpose : To present an expected outcome that researchers aim to support with data.
Example : “Students who receive additional tutoring will perform better academically than those who do not.”
3. Directional Hypothesis
Definition : A directional hypothesis specifies the direction of the expected relationship between variables, predicting either an increase, decrease, positive, or negative effect.
Purpose : To provide a more precise prediction by indicating the expected direction of the relationship.
Example : “Increasing the duration of daily exercise will lead to a decrease in stress levels among adults.”
4. Non-Directional Hypothesis
Definition : A non-directional hypothesis states that there is a relationship between variables but does not specify the direction of the effect.
Purpose : To allow for exploration of the relationship without committing to a particular direction.
Example : “There is a difference in stress levels between adults who exercise regularly and those who do not.”
Examples of Hypotheses in Different Fields
- Null Hypothesis : “There is no difference in anxiety levels between individuals who practice mindfulness and those who do not.”
- Alternative Hypothesis : “Individuals who practice mindfulness will report lower anxiety levels than those who do not.”
- Directional Hypothesis : “Providing feedback will improve students’ motivation to learn.”
- Non-Directional Hypothesis : “There is a difference in motivation levels between students who receive feedback and those who do not.”
- Null Hypothesis : “There is no association between diet and energy levels among teenagers.”
- Alternative Hypothesis : “A balanced diet is associated with higher energy levels among teenagers.”
- Directional Hypothesis : “An increase in employee engagement activities will lead to improved job satisfaction.”
- Non-Directional Hypothesis : “There is a relationship between employee engagement activities and job satisfaction.”
- Null Hypothesis : “The introduction of green spaces does not affect urban air quality.”
- Alternative Hypothesis : “Green spaces improve urban air quality.”
Writing Guide for Hypotheses
Writing a clear, testable hypothesis involves several steps, starting with understanding the research question and selecting variables. Here’s a step-by-step guide to writing an effective hypothesis.
Step 1: Identify the Research Question
Start by defining the primary research question you aim to investigate. This question should be focused, researchable, and specific enough to allow for hypothesis formation.
Example : “Does regular physical exercise improve mental well-being in college students?”
Step 2: Conduct Background Research
Review relevant literature to gain insight into existing theories, studies, and gaps in knowledge. This helps you understand prior findings and guides you in forming a logical hypothesis based on evidence.
Example : Research shows a positive correlation between exercise and mental well-being, which supports forming a hypothesis in this area.
Step 3: Define the Variables
Identify the independent and dependent variables. The independent variable is the factor you manipulate or consider as the cause, while the dependent variable is the outcome or effect you are measuring.
- Independent Variable : Amount of physical exercise
- Dependent Variable : Mental well-being (measured through self-reported stress levels)
Step 4: Choose the Hypothesis Type
Select the hypothesis type based on the research question. If you predict a specific outcome or direction, use a directional hypothesis. If not, a non-directional hypothesis may be suitable.
Example : “Increasing the frequency of physical exercise will reduce stress levels among college students” (directional hypothesis).
Step 5: Write the Hypothesis
Formulate the hypothesis as a clear, concise statement. Ensure it is specific, testable, and focuses on the relationship between the variables.
Example : “College students who exercise at least three times per week will report lower stress levels than those who do not exercise regularly.”
Step 6: Test and Refine (Optional)
In some cases, it may be necessary to refine the hypothesis after conducting a preliminary test or pilot study. This ensures that your hypothesis is realistic and feasible within the study parameters.
Tips for Writing an Effective Hypothesis
- Use Clear Language : Avoid jargon or ambiguous terms to ensure your hypothesis is easily understandable.
- Be Specific : Specify the expected relationship between the variables, and, if possible, include the direction of the effect.
- Ensure Testability : Frame the hypothesis in a way that allows for empirical testing or observation.
- Focus on One Relationship : Avoid complexity by focusing on a single, clear relationship between variables.
- Make It Measurable : Choose variables that can be quantified or observed to simplify data collection and analysis.
Common Mistakes to Avoid
- Vague Statements : Avoid vague hypotheses that don’t specify a clear relationship or outcome.
- Unmeasurable Variables : Ensure that the variables in your hypothesis can be observed, measured, or quantified.
- Overly Complex Hypotheses : Keep the hypothesis simple and focused, especially for beginner researchers.
- Using Personal Opinions : Avoid subjective or biased language that could impact the neutrality of the hypothesis.
Examples of Well-Written Hypotheses
- Psychology : “Adolescents who spend more than two hours on social media per day will report higher levels of anxiety than those who spend less than one hour.”
- Business : “Increasing customer service training will improve customer satisfaction ratings among retail employees.”
- Health : “Consuming a diet rich in fruits and vegetables is associated with lower cholesterol levels in adults.”
- Education : “Students who participate in active learning techniques will have higher retention rates compared to those in traditional lecture-based classrooms.”
- Environmental Science : “Urban areas with more green spaces will report lower average temperatures than those with minimal green coverage.”
A well-formulated hypothesis is essential to the research process, providing a clear and testable prediction about the relationship between variables. Understanding the different types of hypotheses, following a structured writing approach, and avoiding common pitfalls help researchers create hypotheses that effectively guide data collection, analysis, and conclusions. Whether working in psychology, education, health sciences, or any other field, an effective hypothesis sharpens the focus of a study and enhances the rigor of research.
- Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.
- Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE Publications.
- Trochim, W. M. K. (2006). The Research Methods Knowledge Base (3rd ed.). Atomic Dog Publishing.
- McLeod, S. A. (2019). What is a Hypothesis? Retrieved from https://www.simplypsychology.org/what-is-a-hypotheses.html
- Walliman, N. (2017). Research Methods: The Basics (2nd ed.). Routledge.
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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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Step-by-Step Guide: How to Craft a Strong Research Hypothesis
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A research hypothesis is a concise statement about the expected result of an experiment or project. In many ways, a research hypothesis represents the starting point for a scientific endeavor, as it establishes a tentative assumption that is eventually substantiated or falsified, ultimately improving our certainty about the subject investigated.
To help you with this and ease the process, in this article, we discuss the purpose of research hypotheses and list the most essential qualities of a compelling hypothesis. Let’s find out!
How to Craft a Research Hypothesis
Crafting a research hypothesis begins with a comprehensive literature review to identify a knowledge gap in your field. Once you find a question or problem, come up with a possible answer or explanation, which becomes your hypothesis. Now think about the specific methods of experimentation that can prove or disprove the hypothesis, which ultimately lead to the results of the study.
Enlisted below are some standard formats in which you can formulate a hypothesis¹ :
- A hypothesis can use the if/then format when it seeks to explore the correlation between two variables in a study primarily.
Example: If administered drug X, then patients will experience reduced fatigue from cancer treatment.
- A hypothesis can adopt when X/then Y format when it primarily aims to expose a connection between two variables
Example: When workers spend a significant portion of their waking hours in sedentary work , then they experience a greater frequency of digestive problems.
- A hypothesis can also take the form of a direct statement.
Example: Drug X and drug Y reduce the risk of cognitive decline through the same chemical pathways
What are the Features of an Effective Hypothesis?
Hypotheses in research need to satisfy specific criteria to be considered scientifically rigorous. Here are the most notable qualities of a strong hypothesis:
- Testability: Ensure the hypothesis allows you to work towards observable and testable results.
- Brevity and objectivity: Present your hypothesis as a brief statement and avoid wordiness.
- Clarity and Relevance: The hypothesis should reflect a clear idea of what we know and what we expect to find out about a phenomenon and address the significant knowledge gap relevant to a field of study.
Understanding Null and Alternative Hypotheses in Research
There are two types of hypotheses used commonly in research that aid statistical analyses. These are known as the null hypothesis and the alternative hypothesis . A null hypothesis is a statement assumed to be factual in the initial phase of the study.
For example, if a researcher is testing the efficacy of a new drug, then the null hypothesis will posit that the drug has no benefits compared to an inactive control or placebo . Suppose the data collected through a drug trial leads a researcher to reject the null hypothesis. In that case, it is considered to substantiate the alternative hypothesis in the above example, that the new drug provides benefits compared to the placebo.
Let’s take a closer look at the null hypothesis and alternative hypothesis with two more examples:
Null Hypothesis:
The rate of decline in the number of species in habitat X in the last year is the same as in the last 100 years when controlled for all factors except the recent wildfires.
In the next experiment, the researcher will experimentally reject this null hypothesis in order to confirm the following alternative hypothesis :
The rate of decline in the number of species in habitat X in the last year is different from the rate of decline in the last 100 years when controlled for all factors other than the recent wildfires.
In the pair of null and alternative hypotheses stated above, a statistical comparison of the rate of species decline over a century and the preceding year will help the research experimentally test the null hypothesis, helping to draw scientifically valid conclusions about two factors—wildfires and species decline.
We also recommend that researchers pay attention to contextual echoes and connections when writing research hypotheses. Research hypotheses are often closely linked to the introduction ² , such as the context of the study, and can similarly influence the reader’s judgment of the relevance and validity of the research hypothesis.
Seasoned experts, such as professionals at Elsevier Language Services, guide authors on how to best embed a hypothesis within an article so that it communicates relevance and credibility. Contact us if you want help in ensuring readers find your hypothesis robust and unbiased.
References
- Hypotheses – The University Writing Center. (n.d.). https://writingcenter.tamu.edu/writing-speaking-guides/hypotheses
- Shaping the research question and hypothesis. (n.d.). Students. https://students.unimelb.edu.au/academic-skills/graduate-research-services/writing-thesis-sections-part-2/shaping-the-research-question-and-hypothesis
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Writing a Strong Hypothesis Statement
All good theses begins with a good thesis question. However, all great theses begins with a great hypothesis statement. One of the most important steps for writing a thesis is to create a strong hypothesis statement.
What is a hypothesis statement?
A hypothesis statement must be testable. If it cannot be tested, then there is no research to be done.
Simply put, a hypothesis statement posits the relationship between two or more variables. It is a prediction of what you think will happen in a research study. A hypothesis statement must be testable. If it cannot be tested, then there is no research to be done. If your thesis question is whether wildfires have effects on the weather, “wildfires create tornadoes” would be your hypothesis. However, a hypothesis needs to have several key elements in order to meet the criteria for a good hypothesis.
In this article, we will learn about what distinguishes a weak hypothesis from a strong one. We will also learn how to phrase your thesis question and frame your variables so that you are able to write a strong hypothesis statement and great thesis.
What is a hypothesis?
A hypothesis statement posits, or considers, a relationship between two variables.
As we mentioned above, a hypothesis statement posits or considers a relationship between two variables. In our hypothesis statement example above, the two variables are wildfires and tornadoes, and our assumed relationship between the two is a causal one (wildfires cause tornadoes). It is clear from our example above what we will be investigating: the relationship between wildfires and tornadoes.
A strong hypothesis statement should be:
- A prediction of the relationship between two or more variables
A hypothesis is not just a blind guess. It should build upon existing theories and knowledge . Tornadoes are often observed near wildfires once the fires reach a certain size. In addition, tornadoes are not a normal weather event in many areas; they have been spotted together with wildfires. This existing knowledge has informed the formulation of our hypothesis.
Depending on the thesis question, your research paper might have multiple hypothesis statements. What is important is that your hypothesis statement or statements are testable through data analysis, observation, experiments, or other methodologies.
Formulating your hypothesis
One of the best ways to form a hypothesis is to think about “if...then” statements.
Now that we know what a hypothesis statement is, let’s walk through how to formulate a strong one. First, you will need a thesis question. Your thesis question should be narrow in scope, answerable, and focused. Once you have your thesis question, it is time to start thinking about your hypothesis statement. You will need to clearly identify the variables involved before you can begin thinking about their relationship.
One of the best ways to form a hypothesis is to think about “if...then” statements . This can also help you easily identify the variables you are working with and refine your hypothesis statement. Let’s take a few examples.
If teenagers are given comprehensive sex education, there will be fewer teen pregnancies .
In this example, the independent variable is whether or not teenagers receive comprehensive sex education (the cause), and the dependent variable is the number of teen pregnancies (the effect).
If a cat is fed a vegan diet, it will die .
Here, our independent variable is the diet of the cat (the cause), and the dependent variable is the cat’s health (the thing impacted by the cause).
If children drink 8oz of milk per day, they will grow taller than children who do not drink any milk .
What are the variables in this hypothesis? If you identified drinking milk as the independent variable and growth as the dependent variable, you are correct. This is because we are guessing that drinking milk causes increased growth in the height of children.
Refining your hypothesis
Do not be afraid to refine your hypothesis throughout the process of formulation.
Do not be afraid to refine your hypothesis throughout the process of formulation. A strong hypothesis statement is clear, testable, and involves a prediction. While “testable” means verifiable or falsifiable, it also means that you are able to perform the necessary experiments without violating any ethical standards. Perhaps once you think about the ethics of possibly harming some cats by testing a vegan diet on them you might abandon the idea of that experiment altogether. However, if you think it is really important to research the relationship between a cat’s diet and a cat’s health, perhaps you could refine your hypothesis to something like this:
If 50% of a cat’s meals are vegan, the cat will not be able to meet its nutritional needs .
Another feature of a strong hypothesis statement is that it can easily be tested with the resources that you have readily available. While it might not be feasible to measure the growth of a cohort of children throughout their whole lives, you may be able to do so for a year. Then, you can adjust your hypothesis to something like this:
I f children aged 8 drink 8oz of milk per day for one year, they will grow taller during that year than children who do not drink any milk .
As you work to narrow down and refine your hypothesis to reflect a realistic potential research scope, don’t be afraid to talk to your supervisor about any concerns or questions you might have about what is truly possible to research.
What makes a hypothesis weak?
We noted above that a strong hypothesis statement is clear, is a prediction of a relationship between two or more variables, and is testable. We also clarified that statements, which are too general or specific are not strong hypotheses. We have looked at some examples of hypotheses that meet the criteria for a strong hypothesis, but before we go any further, let’s look at weak or bad hypothesis statement examples so that you can really see the difference.
Bad hypothesis 1: Diabetes is caused by witchcraft .
While this is fun to think about, it cannot be tested or proven one way or the other with clear evidence, data analysis, or experiments. This bad hypothesis fails to meet the testability requirement.
Bad hypothesis 2: If I change the amount of food I eat, my energy levels will change .
This is quite vague. Am I increasing or decreasing my food intake? What do I expect exactly will happen to my energy levels and why? How am I defining energy level? This bad hypothesis statement fails the clarity requirement.
Bad hypothesis 3: Japanese food is disgusting because Japanese people don’t like tourists .
This hypothesis is unclear about the posited relationship between variables. Are we positing the relationship between the deliciousness of Japanese food and the desire for tourists to visit? or the relationship between the deliciousness of Japanese food and the amount that Japanese people like tourists? There is also the problematic subjectivity of the assessment that Japanese food is “disgusting.” The problems are numerous.
The null hypothesis and the alternative hypothesis
The null hypothesis, quite simply, posits that there is no relationship between the variables.
What is the null hypothesis?
The hypothesis posits a relationship between two or more variables. The null hypothesis, quite simply, posits that there is no relationship between the variables. It is often indicated as H 0 , which is read as “h-oh” or “h-null.” The alternative hypothesis is the opposite of the null hypothesis as it posits that there is some relationship between the variables. The alternative hypothesis is written as H a or H 1 .
Let’s take our previous hypothesis statement examples discussed at the start and look at their corresponding null hypothesis.
H a : If teenagers are given comprehensive sex education, there will be fewer teen pregnancies .
H 0 : If teenagers are given comprehensive sex education, there will be no change in the number of teen pregnancies .
The null hypothesis assumes that comprehensive sex education will not affect how many teenagers get pregnant. It should be carefully noted that the null hypothesis is not always the opposite of the alternative hypothesis. For example:
If teenagers are given comprehensive sex education, there will be more teen pregnancies .
These are opposing statements that assume an opposite relationship between the variables: comprehensive sex education increases or decreases the number of teen pregnancies. In fact, these are both alternative hypotheses. This is because they both still assume that there is a relationship between the variables . In other words, both hypothesis statements assume that there is some kind of relationship between sex education and teen pregnancy rates. The alternative hypothesis is also the researcher’s actual predicted outcome, which is why calling it “alternative” can be confusing! However, you can think of it this way: our default assumption is the null hypothesis, and so any possible relationship is an alternative to the default.
Step-by-step sample hypothesis statements
Now that we’ve covered what makes a hypothesis statement strong, how to go about formulating a hypothesis statement, refining your hypothesis statement, and the null hypothesis, let’s put it all together with some examples. The table below shows a breakdown of how we can take a thesis question, identify the variables, create a null hypothesis, and finally create a strong alternative hypothesis.
Once you have formulated a solid thesis question and written a strong hypothesis statement, you are ready to begin your thesis in earnest. Check out our site for more tips on writing a great thesis and information on thesis proofreading and editing services.
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Review Checklist
Start with a clear thesis question
Think about “if-then” statements to identify your variables and the relationship between them
Create a null hypothesis
Formulate an alternative hypothesis using the variables you have identified
Make sure your hypothesis clearly posits a relationship between variables
Make sure your hypothesis is testable considering your available time and resources
What makes a hypothesis strong? +
A hypothesis is strong when it is testable, clear, and identifies a potential relationship between two or more variables.
What makes a hypothesis weak? +
A hypothesis is weak when it is too specific or too general, or does not identify a clear relationship between two or more variables.
What is the null hypothesis? +
The null hypothesis posits that the variables you have identified have no relationship.
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4 Alternative hypothesis. An alternative hypothesis, abbreviated as H 1 or H A, is used in conjunction with a null hypothesis. It states the opposite of the null hypothesis, so that one and only one must be true. Examples: Plants grow better with bottled water than tap water. Professional psychics win the lottery more than other people. 5 ...
4. Refine your hypothesis. You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain: The relevant variables; The specific group being studied; The predicted outcome of the experiment or analysis; 5.
Avoid vague or broad statements that cannot be empirically tested. Also, make sure that your hypothesis is potentially falsifiable; i.e., there should exist the possibility that it can be proven wrong. For example, a hypothesis like "Sunflower plants need water to grow" is not falsifiable, as it is already a well-established fact.
A hypothesis refers to a single statement or proposition that is formulated to explain or predict the relationship between variables. On the other hand, hypotheses is the plural form of the term hypothesis, commonly used when multiple statements or propositions are proposed and tested simultaneously. What Is a Good Hypothesis Statement
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process. Consider a study designed to examine the relationship between sleep deprivation and test ...
Characteristics of a hypothesis. So, what makes a good hypothesis? Here are some important characteristics of a hypothesis. 8,9 . Testable: You must be able to test the hypothesis using scientific methods to either accept or reject the prediction. Falsifiable: It should be possible to collect data that reject rather than support the hypothesis.
Hypothesis. A hypothesis is a specific, testable prediction or statement that suggests an expected relationship between variables in a study. It acts as a starting point, guiding researchers to examine whether their predictions hold true based on collected data. For a hypothesis to be useful, it must be clear, concise, and based on prior knowledge or theoretical frameworks.
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 most notable qualities of a strong hypothesis: Testability: Ensure the hypothesis allows you to work towards observable and testable results. Brevity and objectivity: Present your hypothesis as a brief statement and avoid wordiness. Clarity and Relevance: The hypothesis should reflect a clear idea of what we know and what we expect ...
Now that we've covered what makes a hypothesis statement strong, how to go about formulating a hypothesis statement, refining your hypothesis statement, and the null hypothesis, let's put it all together with some examples. The table below shows a breakdown of how we can take a thesis question, identify the variables, create a null ...