• Number System and Arithmetic
  • Probability
  • Mensuration
  • Trigonometry
  • Mathematics

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

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.

People Also View:

Mathematics Maths Formulas Branches of Mathematics

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.

author

Similar Reads

  • 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 Sug 12 min read
  • Alternative Hypothesis: Definition, Types and Examples In statistical hypothesis testing, the alternative hypothesis is an important proposition in the hypothesis test. The goal of the hypothesis test is to demonstrate that in the given condition, there is sufficient evidence supporting the credibility of the alternative hypothesis instead of the defaul 7 min read
  • Level of Significance-Definition, Steps and Examples Level of significance or Statistical significance is an important terminology used in Statistics. Level of significance is the measurement of the statistical significance. The level of significance explains whether the null hypothesis is accepted or rejected. In this article, we are going to discuss 7 min read
  • Cell Theory Notes - Definition, Parts, History, & Examples Cell Theory is a foundational biological principle stating that all living organisms are composed of cells, the cell is the basic unit of life, and all cells arise from pre-existing cells. Developed by scientists Schleiden, Schwann, and Virchow in the 19th century, this theory underscores the role o 8 min read
  • First Derivative: Definition, Formulas, and Examples First Derivative Test is the test in calculus to find whether a function has a maximum or minimum value in the given interval. As the name suggests, the first derivative is used in this test to find the critical point and then further conditions are used to check each critical point for extrema. Man 14 min read
  • Hypothesis Testing Formula Statistics is a discipline of applied mathematics that deals with gathering, describing, analyzing, and inferring conclusions from numerical data. Differential and integral calculus, linear algebra, and probability theory are all used substantially in statistics' mathematical theories. Statisticians 8 min read
  • Difference Between Hypothesis And Theory Understanding the difference between a hypothesis and a theory is important in scientific research. A hypothesis is an educated guess or proposed explanation for a phenomenon, based on limited evidence and requiring further investigation. While, a theory is a well-substantiated explanation of an asp 5 min read
  • Real-life Applications of Hypothesis Testing Hypothesis testing is a fundamental statistical concept that helps us to conclude larger groups based on smaller samples. It offers a systematic approach to conclude population characteristics from observed sample data. It's like making educated guesses and then collecting data to see if our guesses 6 min read
  • Econometrics : Meaning, Examples, Theory and Methods What is Econometrics?Econometrics is a branch of economics that applies statistical methods and mathematical models to analyze economic data. It combines economic theory, mathematics, and statistical techniques to quantify and test hypotheses about economic relationships. Econometric analysis is use 10 min read
  • Real Life Examples and Applications of Power Set The concept of power sets is a fundamental topic in set theory with a wide range of real-life applications. A power set is essentially a set of all possible subsets of a given set, including the empty set and the set itself. This means if you have a set with three elements, its power set will contai 6 min read
  • How do you define and measure your product hypothesis? Hypothesis in product management is like making an educated guess or assumption about something related to a product, such as what users need or how a new feature might work. It's a statement that you can test to see if it's true or not, usually by trying out different ideas and seeing what happens. 11 min read
  • What are Descriptive Analytics? Working and Examples Descriptive analytics helps to identify important patterns and trends in large datasets. In comparison to all other methods of data analysis, descriptive is the most used one. The main task of descriptive analytics is to create metrics and key performance indicators for use in dashboards and busines 10 min read
  • Equal Sets: Definition, Cardinality, and Venn Diagram Equal Set is the relation between two sets that tells us about the equality of two sets i.e., all the elements of both sets are the same and both sets have the same number of elements as well. As we know, a set is a well-defined collection of objects where no two objects can be the same, and sets ca 9 min read
  • What is Binomial Probability Distribution with Example? In a binomial distribution, the probability of achieving success must stay consistent across the trials being examined. For instance, when tossing a coin, the probability of landing heads is always ½ for each trial, as there are only two possible outcomes.Explanation: Probability is the likelihood o 6 min read
  • What is Spontaneity? - Definition, Types, Gibbs Energy Thermodynamics is a discipline of physics that studies heat, work, and temperature, as well as their relationships with energy, radiation, and matter's physical characteristics. The four principles of thermodynamics regulate the behaviour of these quantities, which provide a quantitative description 7 min read
  • Set Theory - Definition, Types, Operations Set Theory is a branch of logical mathematics that studies the collection of objects and operations based on it. A set is simply a collection of objects or a group of objects. For example, a group of players in a football team is a set and the players in the team are its objects. The words collectio 10 min read
  • Probability Theorems | Theorems and Examples What is Probability?Probability can be defined as the possibility of occurrence of an event. Probability is the likelihood or the chances that an uncertain event will occur. The probability of an event always lies between 0 and 1. [Tex]Probability(P)=\frac{Favourable~Outcomes}{Total~Outcomes} [/Tex] 10 min read
  • Introduction of Statistics and its Types Statistics and its Types: Statistics is a branch of math focused on collecting, organizing, and understanding numerical data. It involves analyzing and interpreting data to solve real-life problems, using various quantitative models. Some view statistics as a separate scientific discipline rather th 15+ min read
  • Collection and Presentation of Data We come across a lot of information every day from different sources. Our newspapers, TV, Phone and the Internet, etc are the sources of information in our life. This information can be related to anything, from bowling averages in cricket to profits of the company over the years. These facts and fi 10 min read
  • Geeks Premier League
  • School Learning
  • Geeks Premier League 2023
  • Maths-Class-12

Improve your Coding Skills with Practice

 alt=

What kind of Experience do you want to share?

IMAGES

  1. What is Hypothesis? Functions- Characteristics-types-Criteria

    what does hypothesis mean in literature

  2. 13 Different Types of Hypothesis (2024)

    what does hypothesis mean in literature

  3. What is an Hypothesis

    what does hypothesis mean in literature

  4. Research Hypothesis: Definition, Types, Examples and Quick Tips (2022)

    what does hypothesis mean in literature

  5. Hypothesis

    what does hypothesis mean in literature

  6. SOLUTION: How to write research hypothesis

    what does hypothesis mean in literature

VIDEO

  1. What Is A Hypothesis?

  2. RESEARCH PROCESS AND HYPOTHESIS

  3. What does hypothesis mean?

  4. Literature Review and Hypothesis Development

  5. Concept of Hypothesis

  6. What is CRITICAL PERIOD HYPOTHESIS What does CRITICAL PERIOD HYPOTHESIS mean