hypothesis and statement difference

Research Hypothesis In Psychology: Types, & Examples

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

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

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

Some key points about hypotheses:

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

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

Types of Research Hypotheses

Alternative hypothesis.

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

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

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

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

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

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

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

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

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

Null Hypothesis

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

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

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

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

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

Nondirectional Hypothesis

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

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

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

Directional Hypothesis

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

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

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

Falsifiability

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

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

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

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

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

Can a Hypothesis be Proven?

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

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

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

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

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

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

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

How to Write a Hypothesis

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

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

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

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

More Examples

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

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Q. What is the difference between a thesis statement and a hypothesis statement?

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Answered By: APUS Librarians Last Updated: Apr 15, 2022     Views: 127629

Both the hypothesis statement and the thesis statement answer a research question. 

• A hypothesis is a statement that can be proved or disproved. It is typically used in quantitative research and predicts the relationship between variables.  
• A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research. A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain a hypothesis statement.

NOTE: In some disciplines, the hypothesis is referred to as a thesis statement! This is not accurate but within those disciplines it is understood that "a short, direct sentence that summarizes the main point" will be included.

For more information, see The Research Question and Hypothesis (PDF file from the English Language Support, Department of Student Services, Ryerson University).

How do I write a good thesis statement?

How do I write a good hypothesis statement?

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5.2 - writing hypotheses.

The first step in conducting a hypothesis test is to write the hypothesis statements that are going to be tested. For each test you will have a null hypothesis (\(H_0\)) and an alternative hypothesis (\(H_a\)).

When writing hypotheses there are three things that we need to know: (1) the parameter that we are testing (2) the direction of the test (non-directional, right-tailed or left-tailed), and (3) the value of the hypothesized parameter.

• At this point we can write hypotheses for a single mean (\(\mu\)), paired means(\(\mu_d\)), a single proportion (\(p\)), the difference between two independent means (\(\mu_1-\mu_2\)), the difference between two proportions (\(p_1-p_2\)), a simple linear regression slope (\(\beta\)), and a correlation (\(\rho\)). 
• The research question will give us the information necessary to determine if the test is two-tailed (e.g., "different from," "not equal to"), right-tailed (e.g., "greater than," "more than"), or left-tailed (e.g., "less than," "fewer than").
• The research question will also give us the hypothesized parameter value. This is the number that goes in the hypothesis statements (i.e., \(\mu_0\) and \(p_0\)). For the difference between two groups, regression, and correlation, this value is typically 0.

Hypotheses are always written in terms of population parameters (e.g., \(p\) and \(\mu\)).  The tables below display all of the possible hypotheses for the parameters that we have learned thus far. Note that the null hypothesis always includes the equality (i.e., =).

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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."

This is the Difference Between a Hypothesis and a Theory

What to Know A hypothesis is an assumption made before any research has been done. It is formed so that it can be tested to see if it might be true. A theory is a principle formed to explain the things already shown in data. Because of the rigors of experiment and control, it is much more likely that a theory will be true than a hypothesis.

As anyone who has worked in a laboratory or out in the field can tell you, science is about process: that of observing, making inferences about those observations, and then performing tests to see if the truth value of those inferences holds up. The scientific method is designed to be a rigorous procedure for acquiring knowledge about the world around us.

In scientific reasoning, a hypothesis is constructed before any applicable research has been done. A theory, on the other hand, is supported by evidence: it's a principle formed as an attempt to explain things that have already been substantiated by data.

Toward that end, science employs a particular vocabulary for describing how ideas are proposed, tested, and supported or disproven. And that's where we see the difference between a hypothesis and a theory .

A hypothesis is an assumption, something proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

What is a Hypothesis?

A hypothesis is usually tentative, an assumption or suggestion made strictly for the objective of being tested.

When a character which has been lost in a breed, reappears after a great number of generations, the most probable hypothesis is, not that the offspring suddenly takes after an ancestor some hundred generations distant, but that in each successive generation there has been a tendency to reproduce the character in question, which at last, under unknown favourable conditions, gains an ascendancy. Charles Darwin, On the Origin of Species , 1859 According to one widely reported hypothesis , cell-phone transmissions were disrupting the bees' navigational abilities. (Few experts took the cell-phone conjecture seriously; as one scientist said to me, "If that were the case, Dave Hackenberg's hives would have been dead a long time ago.") Elizabeth Kolbert, The New Yorker , 6 Aug. 2007

What is a Theory?

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, its likelihood as truth is much higher than that of a hypothesis.

It is evident, on our theory , that coasts merely fringed by reefs cannot have subsided to any perceptible amount; and therefore they must, since the growth of their corals, either have remained stationary or have been upheaved. Now, it is remarkable how generally it can be shown, by the presence of upraised organic remains, that the fringed islands have been elevated: and so far, this is indirect evidence in favour of our theory . Charles Darwin, The Voyage of the Beagle , 1839 An example of a fundamental principle in physics, first proposed by Galileo in 1632 and extended by Einstein in 1905, is the following: All observers traveling at constant velocity relative to one another, should witness identical laws of nature. From this principle, Einstein derived his theory of special relativity. Alan Lightman, Harper's , December 2011

Non-Scientific Use

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch (though theory is more common in this regard):

The theory of the teacher with all these immigrant kids was that if you spoke English loudly enough they would eventually understand. E. L. Doctorow, Loon Lake , 1979 Chicago is famous for asking questions for which there can be no boilerplate answers. Example: given the probability that the federal tax code, nondairy creamer, Dennis Rodman and the art of mime all came from outer space, name something else that has extraterrestrial origins and defend your hypothesis . John McCormick, Newsweek , 5 Apr. 1999 In his mind's eye, Miller saw his case suddenly taking form: Richard Bailey had Helen Brach killed because she was threatening to sue him over the horses she had purchased. It was, he realized, only a theory , but it was one he felt certain he could, in time, prove. Full of urgency, a man with a mission now that he had a hypothesis to guide him, he issued new orders to his troops: Find out everything you can about Richard Bailey and his crowd. Howard Blum, Vanity Fair , January 1995

And sometimes one term is used as a genus, or a means for defining the other:

Laplace's popular version of his astronomy, the Système du monde , was famous for introducing what came to be known as the nebular hypothesis , the theory that the solar system was formed by the condensation, through gradual cooling, of the gaseous atmosphere (the nebulae) surrounding the sun. Louis Menand, The Metaphysical Club , 2001 Researchers use this information to support the gateway drug theory — the hypothesis that using one intoxicating substance leads to future use of another. Jordy Byrd, The Pacific Northwest Inlander , 6 May 2015 Fox, the business and economics columnist for Time magazine, tells the story of the professors who enabled those abuses under the banner of the financial theory known as the efficient market hypothesis . Paul Krugman, The New York Times Book Review , 9 Aug. 2009

Incorrect Interpretations of "Theory"

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general use to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

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Writing a hypothesis and prediction

Part of Biology Working scientifically

• A hypothesis is an idea about how something works that can be tested using experiments.
• A prediction says what will happen in an experiment if the hypothesis is correct.

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Presenter 1: We are going to look at the two words "prediction" and "hypothesis". It's important to know the difference between them.

Presenter 2: A hypothesis is an idea about how something works that can be tested using experiments.

Presenter 1: A prediction is a statement of what we think will happen if the hypothesis is correct.

Presenter 2: So you use your hypothesis to make a prediction.

Student 1: I reckon, because there's more oxygen, it'll last longer. So, I'm thinking maybe 40 seconds?

Presenter 1: Here, my hypothesis is that the more air and oxygen candles have, the longer they stay alight.

Presenter 2: So, if my hypothesis is correct, then my prediction is that candles in larger measuring beakers will burn for longer.

Presenter 1: As the volume of air increases, then the time the candle takes to go out also increases. Our graph shows us the pattern in our results.

Presenter 2: The bigger the measuring beaker, the more air and the longer the candle burnt.

Presenter 1: So, we have seen an experiment looking at how long a candle burns under different beakers.

Presenter 2: We have formed a hypothesis and then we have tested it, looking at the difference between the meaning of the word "hypothesis" and the word "prediction".

What's the question?

Science is all about asking questions and then trying to find answers to them. For example:

• Why are there so many different animals on Earth?
• Why is the sky blue?
• Will humans need to live on the moon?

Science can provide answers to some questions, by using observations close Observation Something that can be seen happening. and experiments. Data is collected to help answer these questions.

The scientific method is a useful way of guiding scientists through an investigation. A hypothesis is developed from an idea or question based on an observation . A prediction is then made, an experiment carried out to test this, then the results are analysed and conclusions can be drawn.

A prediction suggests that there is a relationship between which two types of variables?

Independent and dependent variables.

Prediction and hypothesis

More on Working scientifically

Find out more by working through a topic

Planning an experiment

• count 4 of 11

Maths skills for science

• count 5 of 11

Drawing scientific apparatus

• count 6 of 11

Observation and measurement skills

• count 7 of 11

Thesis Vs Hypothesis: Understanding The Basis And The Key Differences

Hypothesis vs. thesis: They sound similar and seem to discuss the same thing. However, these terms have vastly different meanings and purposes. You may have encountered these concepts in school or research, but understanding them is key to executing quality work. 

As an inexperienced writer, the thought of differentiating between hypotheses and theses might seem like an insurmountable task. Fortunately, I am here to help. 

In this article, I’ll discuss hypothesis vs. thesis, break down their differences, and show you how to apply this knowledge to create quality written works. Let’s get to it!

Thesis vs. Hypothesis: Understanding the Basis

The power of a thesis.

A thesis is a foundational element in academic writing and research. It also serves as the linchpin of your argument, encapsulating the central idea or point you aim to prove or disprove throughout your work. 

A thesis statement is typically found at the end of the introduction in an essay or research paper, succinctly summarizing the overarching theme.

Crafting a strong thesis

• Understand the research: Begin by thoroughly comprehending the requirements and objectives of your research. Having a clear understanding of the topic you are arguing or analyzing is crucial.
• Choose a clear topic: Choose one that interests you and aligns with the research’s scope. Clarity and focus are essential in crafting a strong thesis.
• Conduct research: Gather relevant information and sources to develop a deep understanding of your topic. This research will provide the evidence and context for your thesis.
• Identify your position: Determine your stance or position on the topic. Your thesis should express a clear opinion or argument you intend to support throughout your work.
• Narrow down your focus: Refine your topic and thesis more precisely. Avoid broad, generalized statements. Instead, aim for a concise and specific thesis that addresses a particular aspect of the topic.
• Test for validity: Ensuring that you can argue and provide evidence to support your thesis is crucial. It should not be a self-evident or universally accepted fact.
• Write and revise: Craft your thesis statement as a clear, concise sentence summarizing your main argument. Revise and refine it as needed to improve its clarity and strength.

Remember that a strong thesis serves as the foundation for your entire piece of writing, guiding your readers and keeping your work focused and organized.

Hypothesis: The scientific proposition

In contrast, a hypothesis is a tentative proposition or educated guess. It is the initial step in the scientific method, where researchers formulate a hunch to test their assumptions and theories. 

A hypothesis is an assertion that can be proven or disproven through experimentation and observation.

Formulating a hypothesis

• Identify the research question: Identify the research question or problem you want to investigate. Clearly define the scope and boundaries of your inquiry.
• Review existing knowledge: Conduct a literature review to gather information about the topic. Understand the existing body of knowledge and literature in the field.
• Formulate a tentative explanation: Based on your research and understanding of the topic, create a tentative explanation or educated guess about the phenomenon you are studying. This should be a statement that can be falsifiable through experimentation or observation.
• Make it testable: Ensure that your hypothesis is testable and falsifiable. In other words, designing experiments or gathering data supporting or refuting your hypothesis should be possible.
• Specify variables and predictions: Clearly define the variables involved in your hypothesis and make predictions about how changes in these variables will affect the outcome. It also helps in designing experiments and collecting data to test your hypothesis.

Formulating a hypothesis is a crucial step in the scientific method since it directs research and guides efforts to validate theories or uncover new knowledge.

Key Differences Between Thesis vs. Hypothesis

1. Nature of statement

• Thesis: A thesis presents a clear and definitive statement or argument that summarizes the main point of a research paper or essay.
• Hypothesis: A hypothesis is a tentative and testable proposition or educated guess that suggests a possible outcome of an experiment or research study.
• Thesis: The primary purpose of a thesis is to provide a central focus and roadmap for the entire piece of academic writing.
• Hypothesis: The main purpose of a hypothesis is to guide scientific research by proposing a specific prediction that can be tested and validated.

3. Testability

• Thesis: A thesis is not typically subjected to experimentation but serves as a point of argumentation and discussion.
• Hypothesis: A hypothesis, on the other hand, is explicitly designed for testing through experimentation or observation, making it a fundamental part of the scientific method.

4. Research stage

• Thesis: A thesis is usually formulated after extensive research and analysis as a conclusion or summary of findings.
• Hypothesis: A hypothesis is formulated at the beginning of a research project to establish a basis for experimentation and data collection.
• Thesis: A thesis typically encompasses the entire research paper or essay, providing an overarching theme throughout the work.
• Hypothesis: A hypothesis addresses a specific aspect of a research question or problem, guiding the focus of experiments or investigations.

6. Examples

• Thesis: Example of a thesis statement: “The impact of climate change on marine ecosystems is irreversible.”
• Hypothesis: Example of a hypothesis: “If increased temperatures continue, coral reefs will experience bleaching events.”
• Thesis: The thesis represents a conclusion or a well-supported argument and does not aim to be proven or disproven.
• Hypothesis: On the other hand, a hypothesis aims to be tested and validated through empirical evidence. Besides, it can be proven true or false based on the results of experiments or observations.

These differences highlight the distinct roles that the thesis and hypothesis play in academic writing and scientific research, with one providing a point of argumentation and the other guiding the scientific inquiry process.

Can a hypothesis become a thesis?

Yes. A hypothesis can develop into a thesis as it accumulates substantial evidence through research.

Do all research papers require a thesis?

Not necessarily. While most academic papers benefit from a clear thesis, some, like purely descriptive papers, may follow a different structure.

Can a thesis be proven wrong?

Yes. The purpose of a thesis is not only to prove but also to encourage critical analysis. It can be proven wrong with compelling counterarguments and evidence.

How long should a thesis statement be?

A thesis statement should be concise and to the point, typically one or two sentences.

Is a hypothesis only used in scientific research?

Although hypotheses are typically linked to scientific research, they can also be used to verify assumptions and theories in other areas.

Can a hypothesis be vague?

No. When creating a hypothesis, it’s important to make it clear and able to be tested. Developing experiments and making conclusions based on the results can be difficult if the hypothesis needs clarification.

Final Thoughts

In conclusion, understanding the differences between a hypothesis and a thesis is vital to crafting successful research projects and academic papers. While they may seem interchangeable at first glance, these two concepts serve distinct purposes in the research process. 

A hypothesis serves as a testable prediction or explanation, whereas a thesis is the central argument of a paper or project. Your work can lack clarity and purpose without understanding the difference. 

So, the next time you embark on a research project, take the time to ensure that you understand the fundamental difference between a hypothesis and a thesis. Doing so can lead to more focused, meaningful research that advances knowledge and understanding in your field.

You can also learn more about how long a thesis statement should be .

Thanks for reading.

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9.1 Null and Alternative Hypotheses

The actual test begins by considering two hypotheses . They are called the null hypothesis and the alternative hypothesis . These hypotheses contain opposing viewpoints.

H 0 , the — null hypothesis: a statement of no difference between sample means or proportions or no difference between a sample mean or proportion and a population mean or proportion. In other words, the difference equals 0.

H a —, the alternative hypothesis: a claim about the population that is contradictory to H 0 and what we conclude when we reject H 0 .

Since the null and alternative hypotheses are contradictory, you must examine evidence to decide if you have enough evidence to reject the null hypothesis or not. The evidence is in the form of sample data.

After you have determined which hypothesis the sample supports, you make a decision. There are two options for a decision. They are reject H 0 if the sample information favors the alternative hypothesis or do not reject H 0 or decline to reject H 0 if the sample information is insufficient to reject the null hypothesis.

Mathematical Symbols Used in H 0 and H a :

H 0 always has a symbol with an equal in it. H a never has a symbol with an equal in it. The choice of symbol depends on the wording of the hypothesis test. However, be aware that many researchers use = in the null hypothesis, even with > or < as the symbol in the alternative hypothesis. This practice is acceptable because we only make the decision to reject or not reject the null hypothesis.

Example 9.1

H 0 : No more than 30 percent of the registered voters in Santa Clara County voted in the primary election. p ≤ 30 H a : More than 30 percent of the registered voters in Santa Clara County voted in the primary election. p > 30

A medical trial is conducted to test whether or not a new medicine reduces cholesterol by 25 percent. State the null and alternative hypotheses.

Example 9.2

We want to test whether the mean GPA of students in American colleges is different from 2.0 (out of 4.0). The null and alternative hypotheses are the following: H 0 : μ = 2.0 H a : μ ≠ 2.0

We want to test whether the mean height of eighth graders is 66 inches. State the null and alternative hypotheses. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

• H 0 : μ __ 66
• H a : μ __ 66

Example 9.3

We want to test if college students take fewer than five years to graduate from college, on the average. The null and alternative hypotheses are the following: H 0 : μ ≥ 5 H a : μ < 5

We want to test if it takes fewer than 45 minutes to teach a lesson plan. State the null and alternative hypotheses. Fill in the correct symbol ( =, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

• H 0 : μ __ 45
• H a : μ __ 45

Example 9.4

An article on school standards stated that about half of all students in France, Germany, and Israel take advanced placement exams and a third of the students pass. The same article stated that 6.6 percent of U.S. students take advanced placement exams and 4.4 percent pass. Test if the percentage of U.S. students who take advanced placement exams is more than 6.6 percent. State the null and alternative hypotheses. H 0 : p ≤ 0.066 H a : p > 0.066

On a state driver’s test, about 40 percent pass the test on the first try. We want to test if more than 40 percent pass on the first try. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses.

• H 0 : p __ 0.40
• H a : p __ 0.40

Collaborative Exercise

Bring to class a newspaper, some news magazines, and some internet articles. In groups, find articles from which your group can write null and alternative hypotheses. Discuss your hypotheses with the rest of the class.

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The Real Differences Between Thesis and Hypothesis (With table)

A thesis and a hypothesis are two very different things, but they are often confused with one another. In this blog post, we will explain the differences between these two terms, and help you understand when to use which one in a research project.

As a whole, the main difference between a thesis and a hypothesis is that a thesis is an assertion that can be proven or disproven, while a hypothesis is a statement that can be tested by scientific research. 

We probably need to expand a bit on this topic to make things clearer for you, let’s start with definitions and examples.

Definitions

As always, let’s start with the definition of each term before going further.

A thesis is a statement or theory that is put forward as a premise to be maintained or proved. A thesis statement is usually one sentence, and it states your position on the topic at hand.

A hypothesis is a statement that can be tested by scientific research. A hypothesis is usually based on observations, and it seeks to explain how these observations fit together.

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The best way to understand the slight difference between those terms, is to give you an example for each of them.

If you are writing a paper about the effects of climate change on the environment, your thesis might be “Climate change is causing irreparable damage to our planet, and we must take action to prevent further damage”.

If you observe that the leaves on a tree are turning yellow, your hypothesis might be “The tree is sick”. It’s the starting point of experimental research: what can you do then to prove if your hypothesis is right or wrong?

If your hypothesis is correct, then further research should be able to confirm it. However, if your hypothesis is incorrect, research will disprove it. Either way, a hypothesis is an important part of the scientific process.

Taking a look at the etymology of words can help you to remember which one to use is each case.

The word “thesis” comes from the Greek θέσις, meaning “something put forth”, and refers to an intellectual proposition.

The word “hypothesis” comes from the Greek words “hupo,” meaning “under”, and “thesis” that we just explained.

This reflects the fact that a hypothesis is an educated guess, based on observations.

Argumentation vs idea

Hypothesis are generally base on simple observation, while thesis imply that more work has been done on the topic.

A thesis is usually the result of extensive research and contemplation, and seeks to prove a point or theory.

A hypothesis is only a statement that need to be tested by observation or experimentation.

5 mains differences between thesis and hypothesis

Thesis and hypothesis are different in several ways, here are the 5 keys differences between those terms:

• A thesis is a statement that can be argued, while a hypothesis cannot be argued.
• A thesis is usually longer than a hypothesis.
• A thesis is more detailed than a hypothesis.
• A thesis is based on research, while a hypothesis may or may not be based on research.
• A thesis must be proven, while a hypothesis need not be proven.

So, in short, a thesis is an argument, while a hypothesis is a prediction. A thesis is more detailed and longer than a hypothesis, and it is based on research. Finally, a thesis must be proven, while a hypothesis does not need to be proven.

Is there a difference between a thesis and a claim?

Yes, there is a difference between a thesis and a claim. A thesis statement is usually one sentence that states your main argument, while a claim is a more general statement that can be supported by evidence.

Is a hypothesis a prediction?

No, a hypothesis is not a prediction. A prediction is a statement about what you think will happen in the future, whereas a hypothesis is a statement about what you think is causing a particular phenomenon.

What’s the difference between thesis and dissertation?

A thesis is usually shorter and more focused than a dissertation, and it is typically achieved in order to earn a bachelor’s degree. A dissertation is usually longer and more comprehensive, and it is typically completed in order to earn a master’s or doctorate degree.

What is a good thesis statement?

A good thesis statement is specific, debatable, and supports the main point of the paper. It should be clear what the researcher position is, and what evidence they will use to support it.

Thanks for reading! I hope this post helped clear up the differences between thesis and hypothesis. Like that kind of comparison? These other articles might be interesting for you:

• What is the Difference between Mandate and Law?
• The 6 Differences Between Space And Universe
• What’s the Difference Between Cosmology and Astrology?

I am very curious and I love to learn about all types of subjects. Thanks to my experience on the web, I share my discoveries with you on this site :)

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Home » Education » Difference Between Thesis and Hypothesis

Difference Between Thesis and Hypothesis

Main difference –  thesis vs hypothesis                           .

Thesis and hypothesis are two common terms that are often found in research studies. Hypothesis is a logical proposition that is based on existing knowledge that serves as the starting point of an investigation. A thesis is a statement that is put forward as a premise to be maintained or proved. The main difference between thesis and hypothesis is that thesis is found in all research studies whereas a hypothesis is mainly found in experimental quantitative research studies.

This article explains,

1. What is a Thesis?      – Definition, Features, Function

2. What is a Hypothesis?      – Definition, Features, Function

What is a Thesis

The word thesis has two meanings in a research study. Thesis can either refer to a dissertation or a thesis statement. Thesis or dissertation is the long essay or document that consists of the research study.  Thesis can also refer to a theory or statement that is used as a premise to be maintained or proved.

The thesis statement in a research article is a sentence found at the beginning of the paper that presents the main argument of the paper. The rest of the document will gather, organize and present evidence to support this argument. The thesis statement will basically present the topic of the paper and indicate what position the researcher is going to take in relation to this topic. A thesis statement can generally be found at the end of the first paragraph (introductory paragraph) of the paper.

What is a Hypothesis

A hypothesis is a logical assumption based on available evidence. Hypothesis is defined as “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” in the Oxford dictionary and as “an idea or theory that is not proven but that leads to further study or discussion” in the Merriam-Webster dictionary. In simple words, it is an educated guess that is not proven with concrete scientific evidence. Once it is scientifically tested and proven, it becomes a theory. However, it is important to note that a hypothesis can be accurate or inaccurate.

Hypotheses are mostly used in experiments and research studies. However, hypotheses are not used in every research study. They are mostly used in quantitative research studies  that deal with experiments. Hypotheses are often used to test a specific model or theory . They can be used only when the researcher has sufficient knowledge about the subject since hypothesis are always based on the existing knowledge. Once the hypothesis is built, the researcher can find and analyze data and use them to prove or disprove the hypothesis.

Thesis: A thesis is a “statement or theory that is put forward as a premise to be maintained or proved” or a “long essay or dissertation involving personal research, written by a candidate for a university degree” (Oxford dictionary).

Hypothesis: A hypothesis is “a supposition or proposed explanation made on the basis of limited evidence as a starting point for further investigation” (Oxford dictionary).

Thesis: Thesis statement can be found in all research papers.

Hypothesis: Hypotheses are usually found in experimental quantitative research studies.

Thesis: Thesis statement may explain the hypothesis and how the researcher intends to support it.

Hypothesis: Hypothesis is an educated guess based on the existing knowledge.

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Hasanthi is a seasoned content writer and editor with over 8 years of experience. Armed with a BA degree in English and a knack for digital marketing, she explores her passions for literature, history, culture, and food through her engaging and informative writing.

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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 default assumption made by the null hypothesis.

Alternative Hypotheses

Both hypotheses include statements with the same purpose of providing the researcher with a basic guideline. The researcher uses the statement from each hypothesis to guide their research. In statistics, alternative hypothesis is often denoted as H a or H 1 .

Table of Content

What is a Hypothesis?

Alternative hypothesis, types of alternative hypothesis, difference between null and alternative hypothesis, formulating an alternative hypothesis, example of alternative hypothesis, application of alternative hypothesis.

“A hypothesis is a statement of a relationship between two or more variables.” It is a working statement or theory that is based on insufficient evidence.

While experimenting, researchers often make a claim, that they can test. These claims are often based on the relationship between two or more variables. “What causes what?” and “Up to what extent?” are a few of the questions that a hypothesis focuses on answering. The hypothesis can be true or false, based on complete evidence.

While there are different hypotheses, we discuss only null and alternate hypotheses. The null hypothesis, denoted H o , is the default position where variables do not have a relation with each other. That means the null hypothesis is assumed true until evidence indicates otherwise. The alternative hypothesis, denoted H 1 , on the other hand, opposes the null hypothesis. It assumes a relation between the variables and serves as evidence to reject the null hypothesis.

Example of Hypothesis:

Mean age of all college students is 20.4 years. (simple hypothesis).

An Alternative Hypothesis is a claim or a complement to the null hypothesis. If the null hypothesis predicts a statement to be true, the Alternative Hypothesis predicts it to be false. Let’s say the null hypothesis states there is no difference between height and shoe size then the alternative hypothesis will oppose the claim by stating that there is a relation.

We see that the null hypothesis assumes no relationship between the variables whereas an alternative hypothesis proposes a significant relation between variables. An alternative theory is the one tested by the researcher and if the researcher gathers enough data to support it, then the alternative hypothesis replaces the null hypothesis.

Null and alternative hypotheses are exhaustive, meaning that together they cover every possible outcome. They are also mutually exclusive, meaning that only one can be true at a time.

There are a few types of alternative hypothesis that we will see:

1. One-tailed test H 1 : A one-tailed alternative hypothesis focuses on only one region of rejection of the sampling distribution. The region of rejection can be upper or lower.

• Upper-tailed test H 1 : Population characteristic > Hypothesized value
• Lower-tailed test H 1 : Population characteristic < Hypothesized value

2. Two-tailed test H 1 : A two-tailed alternative hypothesis is concerned with both regions of rejection of the sampling distribution.

3. Non-directional test H 1 : A non-directional alternative hypothesis is not concerned with either region of rejection; rather, it is only concerned that null hypothesis is not true.

4. Point test H 1 : Point alternative hypotheses occur when the hypothesis test is framed so that the population distribution under the alternative hypothesis is a fully defined distribution, with no unknown parameters; such hypotheses are usually of no practical interest but are fundamental to theoretical considerations of statistical inference and are the basis of the Neyman–Pearson lemma.

the differences between Null Hypothesis and Alternative Hypothesis is explained in the table below:

Formulating an alternative hypothesis means identifying the relationships, effects or condition being studied. Based on the data we conclude that there is a different inference from the null-hypothesis being considered.

• Understand the null hypothesis.
• Consider the alternate hypothesis
• Choose the type of alternate hypothesis (one-tailed or two-tailed)

Alternative hypothesis must be true when the null hypothesis is false. When trying to identify the information need for alternate hypothesis statement, look for the following phrases:

• “Is it reasonable to conclude…”
• “Is there enough evidence to substantiate…”
• “Does the evidence suggest…”
• “Has there been a significant…”

When alternative hypotheses in mathematical terms, they always include an inequality ( usually ≠, but sometimes < or >) . When writing the alternate hypothesis, make sure it never includes an “=” symbol.

To help you write your hypotheses, you can use the template sentences below.

Does independent variable affect dependent variable?

• Null Hypothesis (H 0 ): Independent variable does not affect dependent variable.
• Alternative Hypothesis (H a ): Independent variable affects dependent variable.

Various examples of Alternative Hypothesis includes:

Two-Tailed Example

• Research Question : Do home games affect a team’s performance?
• Null-Hypothesis: Home games do not affect a team’s performance.
• Alternative Hypothesis: Home games have an effect on team’s performance.
• Research Question: Does sleeping less lead to depression?
• Null-Hypothesis: Sleeping less does not have an effect on depression.
• Alternative Hypothesis : Sleeping less has an effect on depression.

One-Tailed Example

• Research Question: Are candidates with experience likely to get a job?
• Null-Hypothesis: Experience does not matter in getting a job.
• Alternative Hypothesis: Candidates with work experience are more likely to receive an interview.
• Alternative Hypothesis : Teams with home advantage are more likely to win a match.

Some applications of Alternative Hypothesis includes:

• Rejecting Null-Hypothesis : A researcher performs additional research to find flaws in the null hypothesis. Following the research, which uses the alternative hypothesis as a guide, they may decide whether they have enough evidence to reject the null hypothesis.
• Guideline for Research : An alternative and null hypothesis include statements with the same purpose of providing the researcher with a basic guideline. The researcher uses the statement from each hypothesis to guide their research.
• New Theories : Alternative hypotheses can provide the opportunity to discover new theories that a researcher can use to disprove an existing theory that may not have been backed up by evidence.

We defined the relationship that exist between null-hypothesis and alternative hypothesis. While the null hypothesis is always a default assumption about our test data, the alternative hypothesis puts in all the effort to make sure the null hypothesis is disproved.

Null-hypothesis always explores new relationships between the independent variables to find potential outcomes from our test data. We should note that for every null hypothesis, one or more alternate hypotheses can be developed.

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FAQs on Alternative Hypothesis

What is hypothesis.

A hypothesis is a statement of a relationship between two or more variables.” It is a working statement or theory that is based on insufficient evidence.

What is an Alternative Hypothesis?

Alternative hypothesis, denoted by H 1 , opposes the null-hypothesis. It assumes a relation between the variables and serves as an evidence to reject the null-hypothesis.

What is the Difference between Null-Hypothesis and Alternative Hypothesis?

Null hypothesis is the default claim that assumes no relationship between variables while alternative hypothesis is the opposite claim which considers statistical significance between the variables.

What is Alternative and Experimental Hypothesis?

Null hypothesis (H 0 ) states there is no effect or difference, while the alternative hypothesis (H 1 or H a ) asserts the presence of an effect, difference, or relationship between variables. In hypothesis testing, we seek evidence to either reject the null hypothesis in favor of the alternative hypothesis or fail to do so.

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Everyday life and its variability influenced human evolution at least as much as rare activities like big-game  hunting

Professor and Chair of Biology at Seattle Pacific University and Affiliate Assistant Professor of Anthropology, University of Washington

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Cara Wall-Scheffler does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

University of Washington provides funding as a member of The Conversation US.

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Think about taking a walk: where you need to go, how fast you need to move to get there, and whether you need to bring something along to carry the results of your errand.

Are you going on this walk with someone else? Does walking with a friend change your preparation? If you’re walking with a child, do you remember to bring an extra sweater or a snack? You probably did – because people intuitively vary their plan depending on their current needs and situations.

In my research as an anthropologist , I’ve focused on the evolution of human walking and running because I love the flexibility people bring to these behaviors. Humans in all kinds of environments across space and time vary how far they go, when they go and what they go for – whether food, water or friends – based on a multitude of factors, including season, daylight, rituals and family.

Anthropologists split their studies of human activity into two broad categories: what people need to do – including eat, keep their kids alive and so on – and what solutions they come up with to accomplish these needs.

How people keep their children alive is a key issue in my research because it has a direct impact on whether a population survives. It turns out that kids stay alive if they’re with adults. To this end, it is a human universal that women carry heavy loads every day , including kids and their food. This needs-based behavior seems to have been an important part of our evolutionary history and explains quite a few aspects of human physiology and female morphology , such as women’s lower center of mass .

The solutions to other key problems, like specifically which food women will be carrying, vary across time and space. I suggest that these variations are as integral to explaining human biology and culture as the needs themselves.

Impacts of uncommon activities

Evolutionary scientists often focus on how beneficial heritable traits get passed on to offspring when they provide a survival advantage. Eventually a trait can become more common in a population when it provides a useful solution.

For example, researchers have made big claims about how influential persistence hunting via endurance running has been on the way the human body evolved. This theory suggests that taking down prey by running them to exhaustion has led to humans’ own abilities to run long distances – by increasing humans’ ability to sweat, strengthening our head support and making sure our lower limbs are light and elastic.

But persistence hunting occurs in fewer than 2% of the recorded instances of hunting in one major ethnographic database , making it an extremely rare solution to the need to find food. Could such a rare and unusual form of locomotion have had a strong enough impact to select for the suite of adaptive traits that make humans such excellent endurance athletes today?

Maybe persistence hunting is actually a fallback strategy, providing a solution only at key moments when survivorship is on the edge. Or maybe these capabilities are just side effects of the loaded walking done every day . I think a better argument is that the ability to predict how to move between common and uncommon strategies has been the driver of human endurance capacity.

Everyday life’s influence on evolution

Hunting itself, especially of large mammals, is hardly ubiquitous , despite how frequently it is discussed. For example, anthropologists tend to generalize that people who lived in the Arctic even up to a hundred years ago consumed only animal meat hunted by men. But actually, the original ethnographic work reveals a far more nuanced picture .

Women and children were actively involved in hunting, and it was a strongly seasonal activity. Coastal fishing, berry picking and the use of plant materials were all vital to Arctic people’s day-to-day sustenance. Small family groups used canoes for coastal foraging for part of the year.

During other seasons, the whole community participated in hunting large mammals by herding them into dangerous situations where they were more easily killed. Sometimes family groups were together, and sometimes large communities were together. Sometimes women hunted with rifles, and sometimes children ran after caribou.

The dynamic nature of daily life means that the relatively uncommon activity of hunting large terrestrial vertebrates is unlikely to be the main behavior that helps humans solve the key problems of food, water and keeping children alive.

Anthropologist Rebecca Bliege Bird has investigated how predictable food is throughout the day and the year . She’s noted that for most communities, big game is rarely caught, especially when a person is hunting alone. Even among the Hadza in Tanzania, generally considered a big-game hunting community, a hunter acquires 0.03 prey per day on average – essentially 11 animals a year for that person.

Bird and others clearly argue that the planning and flexible coordination done by females is the crucial aspect of how humans survive on a daily basis. It’s the daily efforts of females that allow people to be spontaneous a few times a year to accomplish high-risk activities such as hunting – persistence or otherwise. Therefore it is female flexibility that allows communities to survive between the rare big-game opportunities.

Changing roles and contributions

Some anthropologists argue that in some parts of the world, behavior varies more for cultural reasons , like what tools you make, than for environmental ones, such as how much daylight there is during winter. The importance of culture means that the solutions vary more than the needs.

One of the aspects of culture that varies is the role assigned to specific genders. Varying gender roles are related to the distribution of labor and when people take on certain solution-based tasks . In most cultures, these roles change across a female’s life span. In American culture, this would be like a grandparent going back to college to hone a childhood passion in order to take on a new job to send their grandchildren to college.

In many places, females go from youth when they might carry their siblings and firewood, to early parenthood where they might go hunting with a baby on their back , to older parenthood where they might carry water on their head, a baby on their back and tools in their hands, to postmenopausal periods when they might carry giant loads of mangoes and firewood to and from camp.

Even though always load carrying , our capacity to plan and change our behavior for diverse environments is part of what drives Homo sapiens ’ success, which means that the behavior of females across their different life stages has been a major driver of this capability.

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News 3 Minute Read May | 11 | 2024

An Update on Mr. Rick Slayman, World’s First Recipient of a Genetically-Modified Pig Kidney

Family statement:.

“Our family is deeply saddened about the sudden passing of our beloved Rick but take great comfort knowing he inspired so many. Millions of people worldwide have come to know Rick's story. We felt – and still feel – comforted by the optimism he provided patients desperately waiting for a transplant. To us, Rick was a kind-hearted man with a quick-witted sense of humor who was fiercely dedicated to his family, friends, and co-workers. We are extremely grateful to his care team across Massachusetts General Hospital and Mass General Brigham, especially Dr. Williams, Dr. Kawai, and Dr. Riella, who truly did everything they could to help give Rick a second chance. Their enormous efforts leading the xenotransplant gave our family seven more weeks with Rick, and our memories made during that time will remain in our minds and hearts.

After his transplant, Rick said that one of the reasons he underwent this procedure was to provide hope for the thousands of people who need a transplant to survive. Rick accomplished that goal and his hope and optimism will endure forever. His legacy will be one that inspires patients, researchers, and health care professionals everywhere. Our family asks for respectful privacy as we remember the beautiful soul of our beloved Rick.”

Statement from MGH:

“The Mass General transplant team is deeply saddened at the sudden passing of Mr. Rick Slayman. We have no indication that it was the result of his recent transplant. Mr. Slayman will forever be seen as a beacon of hope to countless transplant patients worldwide and we are deeply grateful for his trust and willingness to advance the field of xenotransplantation. We offer our heartfelt condolences to Mr. Slayman’s family and loved ones as they remember an extraordinary person whose generosity and kindness touched all who knew him.”

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World’s First Genetically-Edited Pig Kidney Transplant into Living Recipient Performed at Massachusetts General Hospital

Massachusetts General Hospital, a founding member of the Mass General Brigham health care system, announced the world’s first successful transplant of a genetically-edited pig (porcine) kidney into a 62-year-old man living with end-stage kidney disease.

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70 years after brown v. board of education, new research shows rise in school segregation.

As the nation prepares to mark the 70th anniversary of the landmark U.S. Supreme Court ruling in Brown v. Board of Education , a new report from researchers at Stanford and USC shows that racial and economic segregation among schools has grown steadily in large school districts over the past three decades — an increase that appears to be driven in part by policies favoring school choice over integration.

Analyzing data from U.S. public schools going back to 1967, the researchers found that segregation between white and Black students has increased by 64 percent since 1988 in the 100 largest districts, and segregation by economic status has increased by about 50 percent since 1991.

The report also provides new evidence about the forces driving recent trends in school segregation, showing that the expansion of charter schools has played a major role.  

The findings were released on May 6 with the launch of the Segregation Explorer , a new interactive website from the Educational Opportunity Project at Stanford University. The website provides searchable data on racial and economic school segregation in U.S. states, counties, metropolitan areas, and school districts from 1991 to 2022. 

“School segregation levels are not at pre- Brown levels, but they are high and have been rising steadily since the late 1980s,” said Sean Reardon , the Professor of Poverty and Inequality in Education at Stanford Graduate School of Education and faculty director of the Educational Opportunity Project. “In most large districts, school segregation has increased while residential segregation and racial economic inequality have declined, and our findings indicate that policy choices – not demographic changes – are driving the increase.” 

“There’s a tendency to attribute segregation in schools to segregation in neighborhoods,” said Ann Owens , a professor of sociology and public policy at USC. “But we’re finding that the story is more complicated than that.”

Assessing the rise

In the Brown v. Board decision issued on May 17, 1954, the U.S. Supreme Court ruled that racially segregated public schools violated the Equal Protection Clause of the Fourteenth Amendment and established that “separate but equal” schools were not only inherently unequal but unconstitutional. The ruling paved the way for future decisions that led to rapid school desegregation in many school districts in the late 1960s and early 1970s.

Though segregation in most school districts is much lower than it was 60 years ago, the researchers found that over the past three decades, both racial and economic segregation in large districts increased. Much of the increase in economic segregation since 1991, measured by segregation between students eligible and ineligible for free lunch, occurred in the last 15 years.

White-Hispanic and white-Asian segregation, while lower on average than white-Black segregation, have both more than doubled in large school districts since the 1980s. 

Racial-economic segregation – specifically the difference in the proportion of free-lunch-eligible students between the average white and Black or Hispanic student’s schools – has increased by 70 percent since 1991. 

School segregation is strongly associated with achievement gaps between racial and ethnic groups, especially the rate at which achievement gaps widen during school, the researchers said.  

“Segregation appears to shape educational outcomes because it concentrates Black and Hispanic students in higher-poverty schools, which results in unequal learning opportunities,” said Reardon, who is also a senior fellow at the Stanford Institute for Economic Policy Research and a faculty affiliate of the Stanford Accelerator for Learning . 

Policies shaping recent trends 

The recent rise in school segregation appears to be the direct result of educational policy and legal decisions, the researchers said. 

Both residential segregation and racial disparities in income declined between 1990 and 2020 in most large school districts. “Had nothing else changed, that trend would have led to lower school segregation,” said Owens. 

But since 1991, roughly two-thirds of districts that were under court-ordered desegregation have been released from court oversight. Meanwhile, since 1998, the charter sector – a form of expanded school choice – has grown.

Expanding school choice could influence segregation levels in different ways: If families sought schools that were more diverse than the ones available in their neighborhood, it could reduce segregation. But the researchers found that in districts where the charter sector expanded most rapidly in the 2000s and 2010s, segregation grew the most. 

The researchers’ analysis also quantified the extent to which the release from court orders accounted for the rise in school segregation. They found that, together, the release from court oversight and the expansion of choice accounted entirely for the rise in school segregation from 2000 to 2019.

The researchers noted enrollment policies that school districts can implement to mitigate segregation, such as voluntary integration programs, socioeconomic-based student assignment policies, and school choice policies that affirmatively promote integration. 

“School segregation levels are high, troubling, and rising in large districts,” said Reardon. “These findings should sound an alarm for educators and policymakers.”

Additional collaborators on the project include Demetra Kalogrides, Thalia Tom, and Heewon Jang. This research, including the development of the Segregation Explorer data and website, was supported by the Russell Sage Foundation, the Robert Wood Johnson Foundation, and the Bill and Melinda Gates Foundation.   

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