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.
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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."
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Hypothesis | Definition, Meaning and Examples
Hypothesis is a hypothesis is fundamental concept in the world of research and statistics. It is a testable statement that explains what is happening or observed. It proposes the relation between the various participating variables.
Hypothesis is also called Theory, Thesis, Guess, Assumption, or Suggestion . Hypothesis creates a structure that guides the search for knowledge.
In this article, we will learn what hypothesis is, its characteristics, types, and examples. We will also learn how hypothesis helps in scientific research.
Table of Content
What is Hypothesis?
Characteristics of hypothesis, sources of hypothesis, types of hypothesis, functions of hypothesis, how hypothesis help in scientific research.
Hypothesis is a suggested idea or an educated guess or a proposed explanation made based on limited evidence, serving as a starting point for further study. They are meant to lead to more investigation.
It's mainly a smart guess or suggested answer to a problem that can be checked through study and trial. In science work, we make guesses called hypotheses to try and figure out what will happen in tests or watching. These are not sure things but rather ideas that can be proved or disproved based on real-life proofs. A good theory is clear and can be tested and found wrong if the proof doesn't support it.
Hypothesis Meaning
A hypothesis is a proposed statement that is testable and is given for something that happens or observed.
- It is made using what we already know and have seen, and it's the basis for scientific research.
- A clear guess tells us what we think will happen in an experiment or study.
- It's a testable clue that can be proven true or wrong with real-life facts and checking it out carefully.
- It usually looks like a "if-then" rule, showing the expected cause and effect relationship between what's being studied.
Here are some key characteristics of a hypothesis:
- Testable: An idea (hypothesis) should be made so it can be tested and proven true through doing experiments or watching. It should show a clear connection between things.
- Specific: It needs to be easy and on target, talking about a certain part or connection between things in a study.
- Falsifiable: A good guess should be able to show it's wrong. This means there must be a chance for proof or seeing something that goes against the guess.
- Logical and Rational: It should be based on things we know now or have seen, giving a reasonable reason that fits with what we already know.
- Predictive: A guess often tells what to expect from an experiment or observation. It gives a guide for what someone might see if the guess is right.
- Concise: It should be short and clear, showing the suggested link or explanation simply without extra confusion.
- Grounded in Research: A guess is usually made from before studies, ideas or watching things. It comes from a deep understanding of what is already known in that area.
- Flexible: A guess helps in the research but it needs to change or fix when new information comes up.
- Relevant: It should be related to the question or problem being studied, helping to direct what the research is about.
- Empirical: Hypotheses come from observations and can be tested using methods based on real-world experiences.
Hypotheses can come from different places based on what you're studying and the kind of research. Here are some common sources from which hypotheses may originate:
- Existing Theories: Often, guesses come from well-known science ideas. These ideas may show connections between things or occurrences that scientists can look into more.
- Observation and Experience: Watching something happen or having personal experiences can lead to guesses. We notice odd things or repeat events in everyday life and experiments. This can make us think of guesses called hypotheses.
- Previous Research: Using old studies or discoveries can help come up with new ideas. Scientists might try to expand or question current findings, making guesses that further study old results.
- Literature Review: Looking at books and research in a subject can help make guesses. Noticing missing parts or mismatches in previous studies might make researchers think up guesses to deal with these spots.
- Problem Statement or Research Question: Often, ideas come from questions or problems in the study. Making clear what needs to be looked into can help create ideas that tackle certain parts of the issue.
- Analogies or Comparisons: Making comparisons between similar things or finding connections from related areas can lead to theories. Understanding from other fields could create new guesses in a different situation.
- Hunches and Speculation: Sometimes, scientists might get a gut feeling or make guesses that help create ideas to test. Though these may not have proof at first, they can be a beginning for looking deeper.
- Technology and Innovations: New technology or tools might make guesses by letting us look at things that were hard to study before.
- Personal Interest and Curiosity: People's curiosity and personal interests in a topic can help create guesses. Scientists could make guesses based on their own likes or love for a subject.
Here are some common types of hypotheses:
Simple Hypothesis
Complex hypothesis, directional hypothesis.
- Non-directional Hypothesis
Null Hypothesis (H0)
Alternative hypothesis (h1 or ha), statistical hypothesis, research hypothesis, associative hypothesis, causal hypothesis.
Simple Hypothesis guesses a connection between two things. It says that there is a connection or difference between variables, but it doesn't tell us which way the relationship goes. Example: Studying more can help you do better on tests. Getting more sun makes people have higher amounts of vitamin D.
Complex Hypothesis tells us what will happen when more than two things are connected. It looks at how different things interact and may be linked together. Example: How rich you are, how easy it is to get education and healthcare greatly affects the number of years people live. A new medicine's success relies on the amount used, how old a person is who takes it and their genes.
Directional Hypothesis says how one thing is related to another. For example, it guesses that one thing will help or hurt another thing. Example: Drinking more sweet drinks is linked to a higher body weight score. Too much stress makes people less productive at work.
Non-Directional Hypothesis
Non-Directional Hypothesis are the one that don't say how the relationship between things will be. They just say that there is a connection, without telling which way it goes. Example: Drinking caffeine can affect how well you sleep. People often like different kinds of music based on their gender.
Null hypothesis is a statement that says there's no connection or difference between different things. It implies that any seen impacts are because of luck or random changes in the information. Example: The average test scores of Group A and Group B are not much different. There is no connection between using a certain fertilizer and how much it helps crops grow.
Alternative Hypothesis is different from the null hypothesis and shows that there's a big connection or gap between variables. Scientists want to say no to the null hypothesis and choose the alternative one. Example: Patients on Diet A have much different cholesterol levels than those following Diet B. Exposure to a certain type of light can change how plants grow compared to normal sunlight.
Statistical Hypothesis are used in math testing and include making ideas about what groups or bits of them look like. You aim to get information or test certain things using these top-level, common words only. Example: The average smarts score of kids in a certain school area is 100. The usual time it takes to finish a job using Method A is the same as with Method B.
Research Hypothesis comes from the research question and tells what link is expected between things or factors. It leads the study and chooses where to look more closely. Example: Having more kids go to early learning classes helps them do better in school when they get older. Using specific ways of talking affects how much customers get involved in marketing activities.
Associative Hypothesis guesses that there is a link or connection between things without really saying it caused them. It means that when one thing changes, it is connected to another thing changing. Example: Regular exercise helps to lower the chances of heart disease. Going to school more can help people make more money.
Causal Hypothesis are different from other ideas because they say that one thing causes another. This means there's a cause and effect relationship between variables involved in the situation. They say that when one thing changes, it directly makes another thing change. Example: Playing violent video games makes teens more likely to act aggressively. Less clean air directly impacts breathing health in city populations.
Hypotheses have many important jobs in the process of scientific research. Here are the key functions of hypotheses:
- Guiding Research: Hypotheses give a clear and exact way for research. They act like guides, showing the predicted connections or results that scientists want to study.
- Formulating Research Questions: Research questions often create guesses. They assist in changing big questions into particular, checkable things. They guide what the study should be focused on.
- Setting Clear Objectives: Hypotheses set the goals of a study by saying what connections between variables should be found. They set the targets that scientists try to reach with their studies.
- Testing Predictions: Theories guess what will happen in experiments or observations. By doing tests in a planned way, scientists can check if what they see matches the guesses made by their ideas.
- Providing Structure: Theories give structure to the study process by arranging thoughts and ideas. They aid scientists in thinking about connections between things and plan experiments to match.
- Focusing Investigations: Hypotheses help scientists focus on certain parts of their study question by clearly saying what they expect links or results to be. This focus makes the study work better.
- Facilitating Communication: Theories help scientists talk to each other effectively. Clearly made guesses help scientists to tell others what they plan, how they will do it and the results expected. This explains things well with colleagues in a wide range of audiences.
- Generating Testable Statements: A good guess can be checked, which means it can be looked at carefully or tested by doing experiments. This feature makes sure that guesses add to the real information used in science knowledge.
- Promoting Objectivity: Guesses give a clear reason for study that helps guide the process while reducing personal bias. They motivate scientists to use facts and data as proofs or disprovals for their proposed answers.
- Driving Scientific Progress: Making, trying out and adjusting ideas is a cycle. Even if a guess is proven right or wrong, the information learned helps to grow knowledge in one specific area.
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
- Initiating Investigations: Hypotheses are the beginning of science research. They come from watching, knowing what's already known or asking questions. This makes scientists make certain explanations that need to be checked with tests.
- Formulating Research Questions: Ideas usually come from bigger questions in study. They help scientists make these questions more exact and testable, guiding the study's main point.
- Setting Clear Objectives: Hypotheses set the goals of a study by stating what we think will happen between different things. They set the goals that scientists want to reach by doing their studies.
- Designing Experiments and Studies: Assumptions help plan experiments and watchful studies. They assist scientists in knowing what factors to measure, the techniques they will use and gather data for a proposed reason.
- Testing Predictions: Ideas guess what will happen in experiments or observations. By checking these guesses carefully, scientists can see if the seen results match up with what was predicted in each hypothesis.
- Analysis and Interpretation of Data: Hypotheses give us a way to study and make sense of information. Researchers look at what they found and see if it matches the guesses made in their theories. They decide if the proof backs up or disagrees with these suggested reasons why things are happening as expected.
- Encouraging Objectivity: Hypotheses help make things fair by making sure scientists use facts and information to either agree or disagree with their suggested reasons. They lessen personal preferences by needing proof from experience.
- Iterative Process: People either agree or disagree with guesses, but they still help the ongoing process of science. Findings from testing ideas make us ask new questions, improve those ideas and do more tests. It keeps going on in the work of science to keep learning things.
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Hypothesis is a testable statement serving as an initial explanation for phenomena, based on observations, theories, or existing knowledge . It acts as a guiding light for scientific research, proposing potential relationships between variables that can be empirically tested through experiments and observations.
The hypothesis must be specific, testable, falsifiable, and grounded in prior research or observation, laying out a predictive, if-then scenario that details a cause-and-effect relationship. It originates from various sources including existing theories, observations, previous research, and even personal curiosity, leading to different types, such as simple, complex, directional, non-directional, null, and alternative hypotheses, each serving distinct roles in research methodology .
The hypothesis not only guides the research process by shaping objectives and designing experiments but also facilitates objective analysis and interpretation of data , ultimately driving scientific progress through a cycle of testing, validation, and refinement.
Hypothesis - FAQs
What is a hypothesis.
A guess is a possible explanation or forecast that can be checked by doing research and experiments.
What are Components of a Hypothesis?
The components of a Hypothesis are Independent Variable, Dependent Variable, Relationship between Variables, Directionality etc.
What makes a Good Hypothesis?
Testability, Falsifiability, Clarity and Precision, Relevance are some parameters that makes a Good Hypothesis
Can a Hypothesis be Proven True?
You cannot prove conclusively that most hypotheses are true because it's generally impossible to examine all possible cases for exceptions that would disprove them.
How are Hypotheses Tested?
Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data
Can Hypotheses change during Research?
Yes, you can change or improve your ideas based on new information discovered during the research process.
What is the Role of a Hypothesis in Scientific Research?
Hypotheses are used to support scientific research and bring about advancements in knowledge.
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What is Hypothesis? Definition, Meaning, Characteristics, Sources
- Post last modified: 10 January 2022
- Reading time: 18 mins read
- Post category: Research Methodology
- What is Hypothesis?
Hypothesis is a prediction of the outcome of a study. Hypotheses are drawn from theories and research questions or from direct observations. In fact, a research problem can be formulated as a hypothesis. To test the hypothesis we need to formulate it in terms that can actually be analysed with statistical tools.
As an example, if we want to explore whether using a specific teaching method at school will result in better school marks (research question), the hypothesis could be that the mean school marks of students being taught with that specific teaching method will be higher than of those being taught using other methods.
In this example, we stated a hypothesis about the expected differences between groups. Other hypotheses may refer to correlations between variables.
Table of Content
- 1 What is Hypothesis?
- 2 Hypothesis Definition
- 3 Meaning of Hypothesis
- 4.1 Conceptual Clarity
- 4.2 Need of empirical referents
- 4.3 Hypothesis should be specific
- 4.4 Hypothesis should be within the ambit of the available research techniques
- 4.5 Hypothesis should be consistent with the theory
- 4.6 Hypothesis should be concerned with observable facts and empirical events
- 4.7 Hypothesis should be simple
- 5.1 Observation
- 5.2 Analogies
- 5.4 State of Knowledge
- 5.5 Culture
- 5.6 Continuity of Research
- 6.1 Null Hypothesis
- 6.2 Alternative Hypothesis
Thus, to formulate a hypothesis, we need to refer to the descriptive statistics (such as the mean final marks), and specify a set of conditions about these statistics (such as a difference between the means, or in a different example, a positive or negative correlation). The hypothesis we formulate applies to the population of interest.
The null hypothesis makes a statement that no difference exists (see Pyrczak, 1995, pp. 75-84).
Hypothesis Definition
A hypothesis is ‘a guess or supposition as to the existence of some fact or law which will serve to explain a connection of facts already known to exist.’ – J. E. Creighton & H. R. Smart
Hypothesis is ‘a proposition not known to be definitely true or false, examined for the sake of determining the consequences which would follow from its truth.’ – Max Black
Hypothesis is ‘a proposition which can be put to a test to determine validity and is useful for further research.’ – W. J. Goode and P. K. Hatt
A hypothesis is a proposition, condition or principle which is assumed, perhaps without belief, in order to draw out its logical consequences and by this method to test its accord with facts which are known or may be determined. – Webster’s New International Dictionary of the English Language (1956)
Meaning of Hypothesis
From the above mentioned definitions of hypothesis, its meaning can be explained in the following ways.
- At the primary level, a hypothesis is the possible and probable explanation of the sequence of happenings or data.
- Sometimes, hypothesis may emerge from an imagination, common sense or a sudden event.
- Hypothesis can be a probable answer to the research problem undertaken for study. 4. Hypothesis may not always be true. It can get disproven. In other words, hypothesis need not always be a true proposition.
- Hypothesis, in a sense, is an attempt to present the interrelations that exist in the available data or information.
- Hypothesis is not an individual opinion or community thought. Instead, it is a philosophical means which is to be used for research purpose. Hypothesis is not to be considered as the ultimate objective; rather it is to be taken as the means of explaining scientifically the prevailing situation.
The concept of hypothesis can further be explained with the help of some examples. Lord Keynes, in his theory of national income determination, made a hypothesis about the consumption function. He stated that the consumption expenditure of an individual or an economy as a whole is dependent on the level of income and changes in a certain proportion.
Later, this proposition was proved in the statistical research carried out by Prof. Simon Kuznets. Matthus, while studying the population, formulated a hypothesis that population increases faster than the supply of food grains. Population studies of several countries revealed that this hypothesis is true.
Validation of the Malthus’ hypothesis turned it into a theory and when it was tested in many other countries it became the famous Malthus’ Law of Population. It thus emerges that when a hypothesis is tested and proven, it becomes a theory. The theory, when found true in different times and at different places, becomes the law. Having understood the concept of hypothesis, few hypotheses can be formulated in the areas of commerce and economics.
- Population growth moderates with the rise in per capita income.
- Sales growth is positively linked with the availability of credit.
- Commerce education increases the employability of the graduate students.
- High rates of direct taxes prompt people to evade taxes.
- Good working conditions improve the productivity of employees.
- Advertising is the most effecting way of promoting sales than any other scheme.
- Higher Debt-Equity Ratio increases the probability of insolvency.
- Economic reforms in India have made the public sector banks more efficient and competent.
- Foreign direct investment in India has moved in those sectors which offer higher rate of profit.
- There is no significant association between credit rating and investment of fund.
Characteristics of Hypothesis
Not all the hypotheses are good and useful from the point of view of research. It is only a few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken. The characteristics of such a useful hypothesis can be listed as below:
Conceptual Clarity
Need of empirical referents, hypothesis should be specific, hypothesis should be within the ambit of the available research techniques, hypothesis should be consistent with the theory, hypothesis should be concerned with observable facts and empirical events, hypothesis should be simple.
The concepts used while framing hypothesis should be crystal clear and unambiguous. Such concepts must be clearly defined so that they become lucid and acceptable to everyone. How are the newly developed concepts interrelated and how are they linked with the old one is to be very clear so that the hypothesis framed on their basis also carries the same clarity.
A hypothesis embodying unclear and ambiguous concepts can to a great extent undermine the successful completion of the research work.
A hypothesis can be useful in the research work undertaken only when it has links with some empirical referents. Hypothesis based on moral values and ideals are useless as they cannot be tested. Similarly, hypothesis containing opinions as good and bad or expectation with respect to something are not testable and therefore useless.
For example, ‘current account deficit can be lowered if people change their attitude towards gold’ is a hypothesis encompassing expectation. In case of such a hypothesis, the attitude towards gold is something which cannot clearly be described and therefore a hypothesis which embodies such an unclean thing cannot be tested and proved or disproved. In short, the hypothesis should be linked with some testable referents.
For the successful conduction of research, it is necessary that the hypothesis is specific and presented in a precise manner. Hypothesis which is general, too ambitious and grandiose in scope is not to be made as such hypothesis cannot be easily put to test. A hypothesis is to be based on such concepts which are precise and empirical in nature. A hypothesis should give a clear idea about the indicators which are to be used.
For example, a hypothesis that economic power is increasingly getting concentrated in a few hands in India should enable us to define the concept of economic power. It should be explicated in terms of measurable indicator like income, wealth, etc. Such specificity in the formulation of a hypothesis ensures that the research is practicable and significant.
While framing the hypothesis, the researcher should be aware of the available research techniques and should see that the hypothesis framed is testable on the basis of them. In other words, a hypothesis should be researchable and for this it is important that a due thought has been given to the methods and techniques which can be used to measure the concepts and variables embodied in the hypothesis.
It does not however mean that hypotheses which are not testable with the available techniques of research are not to be made. If the problem is too significant and therefore the hypothesis framed becomes too ambitious and complex, it’s testing becomes possible with the development of new research techniques or the hypothesis itself leads to the development of new research techniques.
A hypothesis must be related to the existing theory or should have a theoretical orientation. The growth of knowledge takes place in the sequence of facts, hypothesis, theory and law or principles. It means the hypothesis should have a correspondence with the existing facts and theory.
If the hypothesis is related to some theory, the research work will enable us to support, modify or refute the existing theory. Theoretical orientation of the hypothesis ensures that it becomes scientifically useful. According to Prof. Goode and Prof. Hatt, research work can contribute to the existing knowledge only when the hypothesis is related with some theory.
This enables us to explain the observed facts and situations and also verify the framed hypothesis. In the words of Prof. Cohen and Prof. Nagel, “hypothesis must be formulated in such a manner that deduction can be made from it and that consequently a decision can be reached as to whether it does or does not explain the facts considered.”
If the research work based on a hypothesis is to be successful, it is necessary that the later is as simple and easy as possible. An ambition of finding out something new may lead the researcher to frame an unrealistic and unclear hypothesis. Such a temptation is to be avoided. Framing a simple, easy and testable hypothesis requires that the researcher is well acquainted with the related concepts.
Sources of Hypothesis
Hypotheses can be derived from various sources. Some of the sources is given below:
Observation
State of knowledge, continuity of research.
Hypotheses can be derived from observation from the observation of price behavior in a market. For example the relationship between the price and demand for an article is hypothesized.
Analogies are another source of useful hypotheses. Julian Huxley has pointed out that casual observations in nature or in the framework of another science may be a fertile source of hypotheses. For example, the hypotheses that similar human types or activities may be found in similar geophysical regions come from plant ecology.
This is one of the main sources of hypotheses. It gives direction to research by stating what is known logical deduction from theory lead to new hypotheses. For example, profit / wealth maximization is considered as the goal of private enterprises. From this assumption various hypotheses are derived’.
An important source of hypotheses is the state of knowledge in any particular science where formal theories exist hypotheses can be deduced. If the hypotheses are rejected theories are scarce hypotheses are generated from conception frameworks.
Another source of hypotheses is the culture on which the researcher was nurtured. Western culture has induced the emergence of sociology as an academic discipline over the past decade, a large part of the hypotheses on American society examined by researchers were connected with violence. This interest is related to the considerable increase in the level of violence in America.
The continuity of research in a field itself constitutes an important source of hypotheses. The rejection of some hypotheses leads to the formulation of new ones capable of explaining dependent variables in subsequent research on the same subject.
Null and Alternative Hypothesis
Null hypothesis.
The hypothesis that are proposed with the intent of receiving a rejection for them are called Null Hypothesis . This requires that we hypothesize the opposite of what is desired to be proved. For example, if we want to show that sales and advertisement expenditure are related, we formulate the null hypothesis that they are not related.
Similarly, if we want to conclude that the new sales training programme is effective, we formulate the null hypothesis that the new training programme is not effective, and if we want to prove that the average wages of skilled workers in town 1 is greater than that of town 2, we formulate the null hypotheses that there is no difference in the average wages of the skilled workers in both the towns.
Since we hypothesize that sales and advertisement are not related, new training programme is not effective and the average wages of skilled workers in both the towns are equal, we call such hypotheses null hypotheses and denote them as H 0 .
Alternative Hypothesis
Rejection of null hypotheses leads to the acceptance of alternative hypothesis . The rejection of null hypothesis indicates that the relationship between variables (e.g., sales and advertisement expenditure) or the difference between means (e.g., wages of skilled workers in town 1 and town 2) or the difference between proportions have statistical significance and the acceptance of the null hypotheses indicates that these differences are due to chance.
As already mentioned, the alternative hypotheses specify that values/relation which the researcher believes hold true. The alternative hypotheses can cover a whole range of values rather than a single point. The alternative hypotheses are denoted by H 1 .
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2.4 Developing a Hypothesis
Learning objectives.
- Distinguish between a theory and a hypothesis.
- Discover how theories are used to generate hypotheses and how the results of studies can be used to further inform theories.
- Understand the characteristics of a good hypothesis.
Theories and Hypotheses
Before describing how to develop a hypothesis it is imporant to distinguish betwee a theory and a hypothesis. A theory is a coherent explanation or interpretation of one or more phenomena. Although theories can take a variety of forms, one thing they have in common is that they go beyond the phenomena they explain by including variables, structures, processes, functions, or organizing principles that have not been observed directly. Consider, for example, Zajonc’s theory of social facilitation and social inhibition. He proposed that being watched by others while performing a task creates a general state of physiological arousal, which increases the likelihood of the dominant (most likely) response. So for highly practiced tasks, being watched increases the tendency to make correct responses, but for relatively unpracticed tasks, being watched increases the tendency to make incorrect responses. Notice that this theory—which has come to be called drive theory—provides an explanation of both social facilitation and social inhibition that goes beyond the phenomena themselves by including concepts such as “arousal” and “dominant response,” along with processes such as the effect of arousal on the dominant response.
Outside of science, referring to an idea as a theory often implies that it is untested—perhaps no more than a wild guess. In science, however, the term theory has no such implication. A theory is simply an explanation or interpretation of a set of phenomena. It can be untested, but it can also be extensively tested, well supported, and accepted as an accurate description of the world by the scientific community. The theory of evolution by natural selection, for example, is a theory because it is an explanation of the diversity of life on earth—not because it is untested or unsupported by scientific research. On the contrary, the evidence for this theory is overwhelmingly positive and nearly all scientists accept its basic assumptions as accurate. Similarly, the “germ theory” of disease is a theory because it is an explanation of the origin of various diseases, not because there is any doubt that many diseases are caused by microorganisms that infect the body.
A hypothesis , on the other hand, is a specific prediction about a new phenomenon that should be observed if a particular theory is accurate. It is an explanation that relies on just a few key concepts. Hypotheses are often specific predictions about what will happen in a particular study. They are developed by considering existing evidence and using reasoning to infer what will happen in the specific context of interest. Hypotheses are often but not always derived from theories. So a hypothesis is often a prediction based on a theory but some hypotheses are a-theoretical and only after a set of observations have been made, is a theory developed. This is because theories are broad in nature and they explain larger bodies of data. So if our research question is really original then we may need to collect some data and make some observation before we can develop a broader theory.
Theories and hypotheses always have this if-then relationship. “ If drive theory is correct, then cockroaches should run through a straight runway faster, and a branching runway more slowly, when other cockroaches are present.” Although hypotheses are usually expressed as statements, they can always be rephrased as questions. “Do cockroaches run through a straight runway faster when other cockroaches are present?” Thus deriving hypotheses from theories is an excellent way of generating interesting research questions.
But how do researchers derive hypotheses from theories? One way is to generate a research question using the techniques discussed in this chapter and then ask whether any theory implies an answer to that question. For example, you might wonder whether expressive writing about positive experiences improves health as much as expressive writing about traumatic experiences. Although this question is an interesting one on its own, you might then ask whether the habituation theory—the idea that expressive writing causes people to habituate to negative thoughts and feelings—implies an answer. In this case, it seems clear that if the habituation theory is correct, then expressive writing about positive experiences should not be effective because it would not cause people to habituate to negative thoughts and feelings. A second way to derive hypotheses from theories is to focus on some component of the theory that has not yet been directly observed. For example, a researcher could focus on the process of habituation—perhaps hypothesizing that people should show fewer signs of emotional distress with each new writing session.
Among the very best hypotheses are those that distinguish between competing theories. For example, Norbert Schwarz and his colleagues considered two theories of how people make judgments about themselves, such as how assertive they are (Schwarz et al., 1991) [1] . Both theories held that such judgments are based on relevant examples that people bring to mind. However, one theory was that people base their judgments on the number of examples they bring to mind and the other was that people base their judgments on how easily they bring those examples to mind. To test these theories, the researchers asked people to recall either six times when they were assertive (which is easy for most people) or 12 times (which is difficult for most people). Then they asked them to judge their own assertiveness. Note that the number-of-examples theory implies that people who recalled 12 examples should judge themselves to be more assertive because they recalled more examples, but the ease-of-examples theory implies that participants who recalled six examples should judge themselves as more assertive because recalling the examples was easier. Thus the two theories made opposite predictions so that only one of the predictions could be confirmed. The surprising result was that participants who recalled fewer examples judged themselves to be more assertive—providing particularly convincing evidence in favor of the ease-of-retrieval theory over the number-of-examples theory.
Theory Testing
The primary way that scientific researchers use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). A researcher begins with a set of phenomena and either constructs a theory to explain or interpret them or chooses an existing theory to work with. He or she then makes a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researcher then conducts an empirical study to test the hypothesis. Finally, he or she reevaluates the theory in light of the new results and revises it if necessary. This process is usually conceptualized as a cycle because the researcher can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 2.2 shows, this approach meshes nicely with the model of scientific research in psychology presented earlier in the textbook—creating a more detailed model of “theoretically motivated” or “theory-driven” research.
Figure 2.2 Hypothetico-Deductive Method Combined With the General Model of Scientific Research in Psychology Together they form a model of theoretically motivated research.
As an example, let us consider Zajonc’s research on social facilitation and inhibition. He started with a somewhat contradictory pattern of results from the research literature. He then constructed his drive theory, according to which being watched by others while performing a task causes physiological arousal, which increases an organism’s tendency to make the dominant response. This theory predicts social facilitation for well-learned tasks and social inhibition for poorly learned tasks. He now had a theory that organized previous results in a meaningful way—but he still needed to test it. He hypothesized that if his theory was correct, he should observe that the presence of others improves performance in a simple laboratory task but inhibits performance in a difficult version of the very same laboratory task. To test this hypothesis, one of the studies he conducted used cockroaches as subjects (Zajonc, Heingartner, & Herman, 1969) [2] . The cockroaches ran either down a straight runway (an easy task for a cockroach) or through a cross-shaped maze (a difficult task for a cockroach) to escape into a dark chamber when a light was shined on them. They did this either while alone or in the presence of other cockroaches in clear plastic “audience boxes.” Zajonc found that cockroaches in the straight runway reached their goal more quickly in the presence of other cockroaches, but cockroaches in the cross-shaped maze reached their goal more slowly when they were in the presence of other cockroaches. Thus he confirmed his hypothesis and provided support for his drive theory. (Zajonc also showed that drive theory existed in humans (Zajonc & Sales, 1966) [3] in many other studies afterward).
Incorporating Theory into Your Research
When you write your research report or plan your presentation, be aware that there are two basic ways that researchers usually include theory. The first is to raise a research question, answer that question by conducting a new study, and then offer one or more theories (usually more) to explain or interpret the results. This format works well for applied research questions and for research questions that existing theories do not address. The second way is to describe one or more existing theories, derive a hypothesis from one of those theories, test the hypothesis in a new study, and finally reevaluate the theory. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.
To use theories in your research will not only give you guidance in coming up with experiment ideas and possible projects, but it lends legitimacy to your work. Psychologists have been interested in a variety of human behaviors and have developed many theories along the way. Using established theories will help you break new ground as a researcher, not limit you from developing your own ideas.
Characteristics of a Good Hypothesis
There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable . We must be able to test the hypothesis using the methods of science and if you’ll recall Popper’s falsifiability criterion, it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false. Second, a good hypothesis must be logical. As described above, hypotheses are more than just a random guess. Hypotheses should be informed by previous theories or observations and logical reasoning. Typically, we begin with a broad and general theory and use deductive reasoning to generate a more specific hypothesis to test based on that theory. Occasionally, however, when there is no theory to inform our hypothesis, we use inductive reasoning which involves using specific observations or research findings to form a more general hypothesis. Finally, the hypothesis should be positive. That is, the hypothesis should make a positive statement about the existence of a relationship or effect, rather than a statement that a relationship or effect does not exist. As scientists, we don’t set out to show that relationships do not exist or that effects do not occur so our hypotheses should not be worded in a way to suggest that an effect or relationship does not exist. The nature of science is to assume that something does not exist and then seek to find evidence to prove this wrong, to show that really it does exist. That may seem backward to you but that is the nature of the scientific method. The underlying reason for this is beyond the scope of this chapter but it has to do with statistical theory.
Key Takeaways
- A theory is broad in nature and explains larger bodies of data. A hypothesis is more specific and makes a prediction about the outcome of a particular study.
- Working with theories is not “icing on the cake.” It is a basic ingredient of psychological research.
- Like other scientists, psychologists use the hypothetico-deductive method. They construct theories to explain or interpret phenomena (or work with existing theories), derive hypotheses from their theories, test the hypotheses, and then reevaluate the theories in light of the new results.
- Practice: Find a recent empirical research report in a professional journal. Read the introduction and highlight in different colors descriptions of theories and hypotheses.
- Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61 , 195–202. ↵
- Zajonc, R. B., Heingartner, A., & Herman, E. M. (1969). Social enhancement and impairment of performance in the cockroach. Journal of Personality and Social Psychology, 13 , 83–92. ↵
- Zajonc, R.B. & Sales, S.M. (1966). Social facilitation of dominant and subordinate responses. Journal of Experimental Social Psychology, 2 , 160-168. ↵
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What Are the Main Qualities of a Good Hypothesis?
A hypothesis is a fundamental element in the scientific method, guiding researchers in their quest for knowledge. A well-crafted hypothesis serves as the foundation for scientific investigations, influencing experimental design and interpretation of results. In this article, we delve into the main qualities that define a good hypothesis.
1. Clarity and Precision
A good hypothesis should be clear and precise, leaving no room for ambiguity. It must state the expected relationship between variables in a straightforward manner, ensuring that anyone reading it can understand the hypothesis without confusion. Precision is crucial, as it helps to define the scope of the study and guide researchers in their data collection and analysis.
2. Testability
A key characteristic of a good hypothesis is its testability. This means that the hypothesis should be formulated in a way that allows it to be empirically tested through observation or experimentation. A hypothesis that cannot be tested is not scientifically meaningful. Testability ensures that the research process is objective and can contribute to the accumulation of reliable scientific knowledge.
3. Falsifiability
Closely related to testability is the concept of falsifiability. A good hypothesis should be framed in a way that it can be proven false. This may seem counterintuitive, but the ability to be proven wrong is a strength of a hypothesis. It distinguishes scientific hypotheses from unfalsifiable statements and pseudoscience. The scientific method relies on the potential for hypotheses to be rejected based on empirical evidence.
4. Relevance to the Research Question
A good hypothesis is directly related to the research question being investigated. It should address the specific issue or phenomenon under study and provide a clear connection between the variables involved. Irrelevant or off-topic hypotheses can lead to misguided research efforts and misinterpretation of results. Ensuring relevance is crucial for maintaining the focus of the investigation.
5. Parsimony
Parsimony, or simplicity, is a quality that suggests a good hypothesis should be as simple as possible while still accounting for the observed phenomena. The principle of parsimony, also known as Occam’s razor, favors the simplest explanation that fits the evidence. A concise hypothesis is easier to test and more likely to be accurate, contributing to the efficiency and effectiveness of the research process.
6. Logical Consistency
Logical consistency is essential in the formulation of a hypothesis. The components of the hypothesis should align logically, and the hypothesis should not contain internal contradictions. A logically consistent hypothesis enhances the credibility of the research and facilitates a more accurate interpretation of the results.
7. Specificity
A good hypothesis is specific and clearly defines the variables and the expected relationship between them. Vague or overly broad hypotheses can lead to difficulties in testing and may result in inconclusive findings. Specificity ensures that the research has a clear direction and allows for a more precise analysis of the data.
In conclusion, a good hypothesis is a cornerstone of scientific inquiry, guiding researchers toward meaningful discoveries. Clarity, testability, falsifiability, relevance, parsimony, logical consistency, and specificity are key qualities that distinguish a well-formulated hypothesis. Researchers must carefully consider these qualities to ensure that their hypotheses contribute meaningfully to the scientific knowledge base.
Related Reference Links:
- Scientific Method
- Occam’s Razor
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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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Hypothesis: Definition, Characteristics, Types, How to Write
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by Antony W
June 26, 2024
A hypothesis may be an idea or proposal based on limited evidence, but it’s still an important part of a scientific method because it forms the core for future research. It tests the prediction about what your research will find, gives a tentative answer to your research question , but it hasn’t been through testing.
To be very clear, a hypothesis isn’t a standard guess. In addition to basing it on existing theories and knowledge, it should be testable. If you can prove it with direct testing, evidence, and facts, then it’s highly likely a good hypothesis to consider.
In this guide, you’ll learn everything you should know about hypothesis, including what it is, the types, and the right way to write a strong one.
What is a Hypothesis?
A hypothesis is a precise, testable statement presented in the beginning of a study. It is from a hypothesis that one gets a glimpse of the possible outcome of a research process. The hypothesis will propose a relationship between two variables, which can be either dependent or independent variables.
In most cases, you will have to write a hy p othesis in two forms: alternative hypothesis and null hypothesis because they’re experimental in nature.
A hypothesis can be either be accepted or rejected after being experimented against reality. So it’s important to assume there’s no difference between your studies when testing a hypothesis.
What are the Characteristics of a Good Hypothesis?
You now have an idea of what a hypothesis is. Now it’s time to know the main characteristics that describe it.
Below are the 5 major characteristics of a good hypothesis:
- It is should be flexible to allow extended experiments and investigations.
- A hypothesis should not be vague; it is supposed to be particular. With a specific hypothesis, researchers can express specific traits that define ideas.
- One should be able to discuss the hypothesis in a simple and understandable terms
- Includes relationship and variables (for relational hypothesis)
- It should be accurate. A hypothesis that is accurate and clear sounds more reliable.
Where are Hypotheses Derived from?
The main sources of a hypothesis include patterns that affect the way people think, similarities in different circumstances, scientific hypotheses, current experiences, and observation from studies.
The 2 Major Types of Hypothesis
Talking of types of hypotheses, we only have two main types that you should know about to get this right.
1. Alternative Hypothesis
The Alternative hypothesis, designated in the character of H1, gives a glimpse of what to expect from your research.
There are two types of alternative hypothesis:
- Directional hypothesis : A directional hypothesis will help you to gain an understanding of the relationship between variables. Directional hypothesis discusses what to expect in a study.
- Non-directional hypothesis: A non-directional hypothesis won’t give you an idea of what to expect during a study.
2. Null Hypothesis
The null hypothesis is an opposing statement of what you expect from a study. In simple terms, it is the opposite of the alternative hypothesis.
Like the alternative hypothesis, the null hypothesis has a H0 notation, and it states that there’s no authentic connection explained in the hypothesis.
Both null hypothesis and alternative hypotheses bring jaggy illustrations of the topic matter. Also, their main goal is to provide examiners with particular guesses, which they can test in an investigation.
Apart from null and alternative hypotheses, we have other minor hypotheses. These are:
- Complex hypotheses : A complex hypothesis points out the connection between two or more independent and dependent variables.
- Research hypotheses : A research hypothesis tests for the connection between two or more variables.
- Associative and causal hypotheses : An associative and causal hypothesis points out the connection between variables under the scheme when a commute in a variable inexorably changes the other variable. An associative hypothesis highlights the causes and effects of correlation between variables.
- Simple hypotheses : A simple hypothesis shows the relationships between a dependent and an independent variable.
How to Write a Hypothesis
You now have an idea of what a hypothesis is, the types of hypothesis in scientific research, and the importance of a hypothesis.
To take this even further, below are the steps to write a strong hypothesis:
1. Define Your Research Query
The first thing you should always consider no matter the project you are working on is asking the right research question.
We would advise you to use a handful of words and not a block of long a sentence. To make your research question perfect ensure that is specific, manageable, and very clear.
2. Conduct a Basic Initial Research
Before coming up with assumptions you must collect some information and that is because a hypothesis is a prediction of expected results on research.
This is where you get answers to an investigation with the help of what you find out. The data you collect will be of much help because it will not only make logical but also intelligent guesses.
4. Formulate a Hypothesis
Find out what you are likely to find throughout your entire research based on your initial research and use it to make a precise and to-the-point hypothesis.
You can restate the statement in various ways and that depends on the type of assignment and hypothesis you find worth using.
5. Refine the Hypothesis
Doing clarifications is the last step of formulating a hypothesis. This is the part where you ensure your hypothesis points out connections between its variables, the variable is to the purpose and clear, it is valid and particular and it proposes a foreseen outcome of the research.
Final Thoughts
Formulating a strong hypothesis is not as easy, but that doesn’t mean you can’t get it right on a first attempt.
Here are some tips to help:
The first thing will be finding what is more interesting to you. The worst mistake most students or researchers do is picking a topic randomly. We are 99% sure that a topic picked randomly won’t come up with a good hypothesis.
Let the research you did guide you to put down your hypothesis while you keep it clear and direct to the point.
Cut your reader a slack by clearly defining your variables. Unclear variables make your hypothesis look sound terrible.
Consider writing your hypothesis an ‘if’ statement or ‘then’ statement. E.g. If this, then look forward to that as the result.
About the author
Antony W is a professional writer and coach at Help for Assessment. He spends countless hours every day researching and writing great content filled with expert advice on how to write engaging essays, research papers, and assignments.
COMMENTS
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 ...
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.
Characteristics of Hypothesis. Here are some key characteristics of a hypothesis: Testable: An idea (hypothesis) should be made so it can be tested and proven true through doing experiments or watching. It should show a clear connection between things. ... Acquired and Inherited Traits - Definition, Differences, Examples.
Characteristics of Hypothesis. Not all the hypotheses are good and useful from the point of view of research. It is only a few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken. The characteristics of such a useful hypothesis can be listed as below: Conceptual Clarity; Need of empirical ...
Characteristics of a Good Hypothesis. There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable. We must be able to test the hypothesis using the methods of science and if you'll recall Popper's falsifiability criterion, it must be possible to gather evidence that will disconfirm ...
A hypothesis is a fundamental element in the scientific method, guiding researchers in their quest for knowledge. A well-crafted hypothesis serves as the foundation for scientific investigations, influencing experimental design and interpretation of results. In this article, we delve into the main qualities that define a good hypothesis. 1.
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.
Below are the 5 major characteristics of a good hypothesis: It is should be flexible to allow extended experiments and investigations. A hypothesis should not be vague; it is supposed to be particular. With a specific hypothesis, researchers can express specific traits that define ideas.
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.
Characteristics of a Good Hypothesis. There are three general characteristics of a good hypothesis. First, a good hypothesis must be testable and falsifiable.We must be able to test the hypothesis using the methods of science, and it must be possible to gather evidence that will disconfirm the hypothesis if it is indeed false.