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Hypothesis: meaning, criteria for formulation and it’s types.

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Read this article to learn about the meaning, criteria for formulation and types of hypothesis.

Meaning of Hypothesis:

In order to make the problem explicit and in order to focus attention in its solution, it is essential to start with certain known theories. Research, in real terms, depends upon a continuous interplay of theory and facts, upon a continuous stimulation of facts by theory and theory by facts. Theory is initiated by facts and facts lead to the rejection or reformulation of existing theory. Facts may also redefine or clarify the theory.

Hampel has compared a scientific theory to a network in which the terms and concepts are represented by knots and definitions and hypothesis by threads connecting the knots. From certain observational data we derive an interpretative string to some points in the theoretical framework. Then we proceed through definitions and hypothesis to other points from which another interpretative string permits to the plane of observation.

Theory thus gives meaning to empirically observed facts and puts them systematically. Theory is also built upon facts and various facts put in a theoretically framework may be analyzed and interpreted in a logical manner. Grounded on old facts and with the help of theoretical framework, new facts are discovered. In the process, certain deductions are formulated which are called hypotheses.

Thus “after internalizing the problem, after turning back on experience for possible solutions, after observing relevant phenomena, the scientist may formulate a hypothesis.” “A Hypothesis is a conjectural statement, a tentative proposition about relation between two or more phenomena or variables”. It is a tentative generalization, the validity of which remains to be tested.

At its initial stage, a hypothesis may be an imagined idea or a hunch or a mere guess. It is in the form of a declarative sentence and always indicates relation of one or more variable(s) with other variable(s) in a general or specific way. It is mostly based on accumulated knowledge. A hypothesis is made to examine the correct explanation of a phenomenon through investigation, to observe facts on the basis of collected data. If on the basis of verification, the hypothesis is found to be valid, a theory is obtained. Thus, hypothesis a theory entertained in order to study the facts and find out the validity of the theory.

The etymological meaning of hypothesis, therefore, is a theory which is not full reasoned, derived out of the combination of two words ‘hypo’ and ‘thesis’ meaning ‘less than’ and ‘reasoned theory of rational view point’ respectively. Accordingly Mill defines hypothesis as “any supposition which we make (either without actual evidence or an evidence avowedly insufficient) in order to endeavor to deduce conclusions in accordance with facts which are known to be real, under the idea that if the conclusions to which the hypothesis leads are known truths, the hypothesis itself either must be or at least likely to be, true”. Likewise, Goode and Hatt define it as “a proposition which can be put to test to determine validity”.

P.V. Young says that a hypothesis “is provisional central idea which becomes the basis for fruitful investigation, known as working theory” Coffey defines hypothesis as “an attempt at explanation : a provisional supposition made in order to explain scientifically some facts or phenomena”. Hypothesis is not a theory; rather hypotheses are linked and related to theory which is more elaborate in nature as compared to hypothesis.

Therefore William H. George, while distinguishing between theory and hypothesis, described theory as ‘elaborate hypothesis’. Hypothesis is not a claim of truth, but a claim for truth and hence serves as a bridge in the process of investigation which begins with a problem and ends with resolution of the problem. In the words of Cohen and Nagel “a hypothesis directs our search for the order.”

Criteria for Formulation of Hypothesis :

There exist two criteria for formulation of a good hypothesis. First, it is a statement about the relations between variables. Secondly it carries clear implications for testing the stated relations. Thus, these couple of criteria imply that the hypotheses comprise two or more variables which are measurable or potentially measurable and that they specify the way in which they are related. A statement which fails to meet these criteria is no scientific hypothesis in the true sense of the term. However, there are legitimate hypotheses, formulated in factor analytic studies.

The following examples may be cited in order to justify how the couple of criteria apply to hypotheses:

1. More intelligent persons will be less hostile than those of lower level of intelligence.

2. Group study contributes to higher grade achievement.

In the first hypothesis, we visualize a relation stated between one variable, ‘intelligence’, and another variable ‘hostility.’ Furthermore, measurement of these variables is also easily conceivable. In the second example, a relation has also been stated between the variables ‘group study’ and ‘grade achievement.’ There exists the possibility of the measurement of the variables are thus there is implication for testing the hypotheses. Thus both the criteria are satisfied. ‘

Types of Hypothesis :

Hypotheses may be of various kinds. It may be crude or refined. A crude hypothesis is at the lower level of abstraction, indicating only the kind of data to be collected, not leading to higher theoretical research. On the contrary, the refined hypothesis appears to be more significant in research.

It may be in the form of describing something in a given instance, that a particular object, situation or event has certain characteristics. It may be in the form of counting the frequencies or of association among the variables. It may be in the form of causal relationship that a particular characteristic or occurrence is one of the causes determining the other.

On the basis of levels of abstraction, Goode and Hatt have distinguished three broad types of hypotheses.

First, there are the simple levels of hypotheses indicating merely the uniformity in social behaviour. They are the most exact and the least abstract, as they state the existence of presence of empirical uniformities. Often it is said that such hypotheses do not involve much verification or do not require testing at all and they merely add up facts. But it is not correct to say so. Even empirical researches describing certain facts need testing of hypotheses and testing may result in providing with an altogether different profile.

Secondly, there are complex ideal hypotheses at a higher level of abstraction. These are more complex and aim at testing the existence of logically derived relationships between empirical uniformities. They are in the form of generalization, and therefore are also a little abstract. But empirical relationships are important in their context. Such hypotheses are useful in developing tools of analysis and in providing constructs for further hypothesizing.

Thirdly, there are hypotheses which are very complex and quite abstract. They are concerned with the interrelations of multiple analytic variables. They lead to the formulation of a relationship between changes in one property and changes in another.

The above kinds of hypotheses may be explained in an example. On the basis of empirical data we may show statistical regularity by wealth, religion region, size of community culture, tradition, health etc. First, we may formulate hypotheses in a simple manner on the basis of statistical regularity. Secondly, in order to formulate a complex ideal hypothesis we may combine all the factors together. As regards the formulation of the third category of hypothesis, more abstraction is brought in.

Only one of the factors can be studied at a time, such as relationship between religion and fertility or wealth and fertility, and all other variables may be controlled. Obviously, it is a very abstract way of handling the problem, because people may be affected by a multiplicity of variables. Yet, we are interested in studying the cause and effect relationship of one factor at one time. Hence, this level of hypothesizing is not only more abstract, simultaneously it is more sophisticated and provides scope for further research.

Related Articles:

• Conditions for a Valid Hypothesis: 5 Conditions
• Sources of Hypothesis in Social Research: 4 Sources

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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, 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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How to Write a Great Hypothesis

Hypothesis Definition, Format, Examples, and Tips

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

Verywell / Alex Dos Diaz

• The Scientific Method

Hypothesis Format

Falsifiability of a hypothesis.

• Operationalization

Hypothesis Types

Hypotheses examples.

• Collecting Data

A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.

Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."

At a Glance

A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.

The Hypothesis in the Scientific Method

In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:

• Forming a question
• Performing background research
• Creating a hypothesis
• Designing an experiment
• Collecting data
• Analyzing the results
• Drawing conclusions
• Communicating the results

The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.

Unless you are creating an exploratory study, your hypothesis should always explain what you  expect  to happen.

In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.

Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.

In many cases, researchers may find that the results of an experiment  do not  support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.

In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."

In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."

Elements of a Good Hypothesis

So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:

• Is your hypothesis based on your research on a topic?
• Can your hypothesis be tested?
• Does your hypothesis include independent and dependent variables?

Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the  journal articles you read . Many authors will suggest questions that still need to be explored.

How to Formulate a Good Hypothesis

To form a hypothesis, you should take these steps:

• Collect as many observations about a topic or problem as you can.
• Evaluate these observations and look for possible causes of the problem.
• Create a list of possible explanations that you might want to explore.
• After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.

In the scientific method ,  falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.

Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that  if  something was false, then it is possible to demonstrate that it is false.

One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.

The Importance of Operational Definitions

A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.

Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.

For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.

These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.

Replicability

One of the basic principles of any type of scientific research is that the results must be replicable.

Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.

Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.

To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.

Hypothesis Checklist

• Does your hypothesis focus on something that you can actually test?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate the variables?
• Can your hypothesis be tested without violating ethical standards?

The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:

• Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
• Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
• Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
• Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
• Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
• Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.

A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the  dependent variable  if you change the  independent variable .

The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."

A few examples of simple hypotheses:

• "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
• "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."​
• "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
• "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."

Examples of a complex hypothesis include:

• "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
• "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."

Examples of a null hypothesis include:

• "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
• "There is no difference in scores on a memory recall task between children and adults."
• "There is no difference in aggression levels between children who play first-person shooter games and those who do not."

Examples of an alternative hypothesis:

• "People who take St. John's wort supplements will have less anxiety than those who do not."
• "Adults will perform better on a memory task than children."
• "Children who play first-person shooter games will show higher levels of aggression than children who do not." 

Collecting Data on Your Hypothesis

Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.

Descriptive Research Methods

Descriptive research such as  case studies ,  naturalistic observations , and surveys are often used when  conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.

Once a researcher has collected data using descriptive methods, a  correlational study  can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.

Experimental Research Methods

Experimental methods  are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).

Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually  cause  another to change.

The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.

Thompson WH, Skau S. On the scope of scientific hypotheses .  R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607

Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:].  Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z

Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004

Nosek BA, Errington TM. What is replication ?  PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691

Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies .  Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18

Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Definition of a Hypothesis

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A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence.

Within social science, a hypothesis can take two forms. It can predict that there is no relationship between two variables, in which case it is a null hypothesis . Or, it can predict the existence of a relationship between variables, which is known as an alternative hypothesis.

In either case, the variable that is thought to either affect or not affect the outcome is known as the independent variable, and the variable that is thought to either be affected or not is the dependent variable.

Researchers seek to determine whether or not their hypothesis, or hypotheses if they have more than one, will prove true. Sometimes they do, and sometimes they do not. Either way, the research is considered successful if one can conclude whether or not a hypothesis is true. 

Null Hypothesis

A researcher has a null hypothesis when she or he believes, based on theory and existing scientific evidence, that there will not be a relationship between two variables. For example, when examining what factors influence a person's highest level of education within the U.S., a researcher might expect that place of birth, number of siblings, and religion would not have an impact on the level of education. This would mean the researcher has stated three null hypotheses.

Alternative Hypothesis

Taking the same example, a researcher might expect that the economic class and educational attainment of one's parents, and the race of the person in question are likely to have an effect on one's educational attainment. Existing evidence and social theories that recognize the connections between wealth and cultural resources , and how race affects access to rights and resources in the U.S. , would suggest that both economic class and educational attainment of the one's parents would have a positive effect on educational attainment. In this case, economic class and educational attainment of one's parents are independent variables, and one's educational attainment is the dependent variable—it is hypothesized to be dependent on the other two.

Conversely, an informed researcher would expect that being a race other than white in the U.S. is likely to have a negative impact on a person's educational attainment. This would be characterized as a negative relationship, wherein being a person of color has a negative effect on one's educational attainment. In reality, this hypothesis proves true, with the exception of Asian Americans , who go to college at a higher rate than whites do. However, Blacks and Hispanics and Latinos are far less likely than whites and Asian Americans to go to college.

Formulating a Hypothesis

Formulating a hypothesis can take place at the very beginning of a research project , or after a bit of research has already been done. Sometimes a researcher knows right from the start which variables she is interested in studying, and she may already have a hunch about their relationships. Other times, a researcher may have an interest in ​a particular topic, trend, or phenomenon, but he may not know enough about it to identify variables or formulate a hypothesis.

Whenever a hypothesis is formulated, the most important thing is to be precise about what one's variables are, what the nature of the relationship between them might be, and how one can go about conducting a study of them.

Updated by Nicki Lisa Cole, Ph.D

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• What is Hypothesis?
• Post last modified: 20 April 2021
• Reading time: 20 mins read
• Post category: Research Methodology

Hypothesis is a proposition which can be put to a test to determine validity and is useful for further research.

Hypothesis is a statement which can be proved or disproved. It is a statement capable of being tested. In a sense, hypothesis is a question which definitely has an answer. Hypothesis aids us a great deal while collecting, tabulating and analyzing data and other relevant information.

Table of Content

• 1 What is Hypothesis?
• 2 Hypothesis Definition
• 3 Meaning of Hypothesis
• 4.1 Conceptual Clarity
• 4.2 Need of the 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 Formulation of Hypothesis
• 6 Null Hypothesis
• 7.1 Stating the hypothesis of interest
• 7.2 Collection of relevant data and information
• 7.3 Formation of null hypothesis
• 7.4 Alternative Hypothesis
• 7.5 Selection of suitable test statistic
• 7.6 Determine the level of significance
• 7.7 Decision

Hypothesis thus is inevitable in any kind of research, if it is to be carried out successfully. The meaning and exact nature of hypothesis will become clear from the following definitions.

Hypothesis Definition

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.
• 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.

Characteristics of Hypothesis

Not all the hypotheses are good and useful from the point of view of research. It is only the few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken.

The characteristics of a good hypothesis can be listed as below.

Conceptual Clarity

Need of the 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 unclear 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 few hands in India should enable us to define the concept of economic power. It should be explicated in terms of the measurable indicator like income, wealth, etc. Such specificity in the formulation of 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 the 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 to 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.

Formulation of Hypothesis

The real beginning of any research is made with the formulation of hypothesis. In a sense, research is nothing but accepting the hypothesis by proving it or rejecting it if it is disproved or modifying it.

Moreover, in any type of research work, the information and data is to be collected with reference to the hypothesis and the concepts embodied in it. Hypothesis therefore occupies an important place in any type of research.

Formulation of hypothesis, however, requires that the difficulties encountered are overcome. A researcher may suffer from a number of difficulties at the stage of formulating a good hypothesis

• The researcher should have a thorough knowledge of the accepted theories and basic concepts of that research area where he has decided to work in.
• The researcher should also acquire the logical and scientific thinking power to frame a hypothesis based on the theories and basic concepts known to him.
• The researcher should also be well acquainted with the available research methods and techniques.

Normally, the hypothesis made in the beginning of research is of crude or working nature. Such a working hypothesis is to be made while planning a research work. As the research work proceeds with the working hypothesis, new information, data and evidence becomes available. In the light of new information and evidence, the working hypothesis is to be modified and revised.

Sometimes, the working hypothesis changes in a significant way after the modifications are made. In some researches, the hypothesis is formulated not in the beginning but at the time of classification and analysis of data and information.

In the case of such a hypothesis also it becomes necessary that new or additional information is collected. It thus implies that every hypothesis is subject to change. In order to put the research work in an operative mode, several alternative hypotheses are made in the beginning.

While framing such hypotheses utmost care is to be taken while using the concepts. The nature of the hypothesis should be such that it enables the researcher to find out something new, something which is previously unknown.

In the context of research work and while performing the hypothesis testing exercise, both the alternative hypothesis which is to be proved and accepted and null hypothesis, which is to be disproved, are important and required.

The main hypothesis of the research work is the research hypothesis or the alternative hypothesis. Researcher’s job is to collect information and data so as to prove the alternative hypothesis so that it can be accepted. Null hypothesis on the other hand is the exact opposite of research or alternative hypothesis.

Null hypothesis is also called a hypothesis with no difference. Like the research or alternative hypothesis, the null hypothesis is also a statement.

The logic behind formulating a null hypothesis is that it is always easy to prove that a statement is wrong than to prove that a statement (research hypothesis) is cent percent true.

In short, while framing hypothesis for research work, it is important that at least two hypotheses are framed, one of which is a null hypothesis and the other one is an alternative hypothesis.

For instance, a null hypothesis and alternative hypothesis can be as below.

Null Hypothesis

The average age of entry in to the labour market of commerce graduates is 22 years.

However, the collected data and information, when analysed, reveals that Hypothesis the average entry age is greater than or less than 22 years, then the null hypothesis gets rejected.

In such a case the alternative hypothesis can be as under

• The average age of entry into the labour market is greater than 22 years (> 22)
• The average age of entry into the labour market is less than 22 years (< 22)
• The average age of entry into the labour market is not 22 years (‘“ 22)

Test of Hypothesis

As stated in the beginning, the hypothesis formulation marks the beginning of any research. After the hypothesis is formulated in the context of a research problem, next process involves a collection of relevant data and information and analysis of the same using an appropriate statistical technique, which proves or disproves the hypothesis formulated in the beginning.

The testing of hypothesis thus represents the end of the research work. Testing of hypothesis can be considered as the most important step in any type of research work as it determines the fruitfulness of the research work.

Unless the hypothesis is tested, it will only remain an inference or a proposition. The act of determining the validity of the hypothesis based on the collected data is called the testing of hypothesis.

The exercise of hypothesis testing is a systematic work and normally involves following stages or steps:

Stating the hypothesis of interest

Collection of relevant data and information, formation of null hypothesis, alternative hypothesis, selection of suitable test statistic, determine the level of significance.

Based on the research problem and a primitive understanding of the relationship between the variables involved, a researcher formulates a hypothesis of interest or a research hypothesis which he wants to prove.

Given the research problem and the formulated hypothesis of interest, the next step is to collect the relevant data and information to proceed further towards the end objective (i.e. proving the research hypothesis).

For the testing purpose, a null hypothesis is formed based on the statistical data. The null hypothesis is also called as the hypothesis with no difference.

In other words, null hypothesis states that there is no difference between the variables involved in the hypothesis or the variables are not related.

For example, if the research hypothesis is that the commerce graduates are more employable than the arts graduates, then the null hypothesis will be that both are equally employable or that there is no difference in the employment opportunities available to both.

If in research hypothesis, price and demand are said to be inversely related, the null hypothesis assumes them independent or states that price and demand are not related.

After the formulation of null hypothesis, alternative hypothesis can be derived. Alternative hypothesis is the negation of null hypothesis and can be more than one and conform to the research hypothesis.

In the example of employability, the alternative hypothesis can be

• commerce graduates are more employable or arts graduates are more employable
• commerce graduates are having more employability
• arts graduates are having more employability.

The next step in the hypothesis testing exercise is that of selecting an appropriate statistical test. It can be chi-square test, t-test or f-test or any other test. Such a test is carried out at a given level of significance.

As stated in the above step a statistical test is conducted at a given level of significance

• A level of significance indicates the probability of rejecting or accepting the null hypothesis.

The last step in testing hypothesis is that of taking a decision on the basis of the given level of significance

• It is seen whether the null hypothesis falls in the accepting region or in rejecting region and accordingly a decision is taken. In this way, the acceptance or rejection of null hypothesis determines the acceptance or rejection of the initial research hypothesis.

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• Classical Management Approach
• Is Management an Art or Science?
• Who is a Manager?

Operations Research

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

Operation Management

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

Service Operations Management

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

Procurement Management

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

Strategic Management

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

Supply Chain

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

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