Statistics Made Easy
How to Write Hypothesis Test Conclusions (With Examples)
A hypothesis test is used to test whether or not some hypothesis about a population parameter is true.
To perform a hypothesis test in the real world, researchers obtain a random sample from the population and perform a hypothesis test on the sample data, using a null and alternative hypothesis:
- Null Hypothesis (H 0 ): The sample data occurs purely from chance.
- Alternative Hypothesis (H A ): The sample data is influenced by some non-random cause.
If the p-value of the hypothesis test is less than some significance level (e.g. α = .05), then we reject the null hypothesis .
Otherwise, if the p-value is not less than some significance level then we fail to reject the null hypothesis .
When writing the conclusion of a hypothesis test, we typically include:
- Whether we reject or fail to reject the null hypothesis.
- The significance level.
- A short explanation in the context of the hypothesis test.
For example, we would write:
We reject the null hypothesis at the 5% significance level. There is sufficient evidence to support the claim that…
Or, we would write:
We fail to reject the null hypothesis at the 5% significance level. There is not sufficient evidence to support the claim that…
The following examples show how to write a hypothesis test conclusion in both scenarios.
Example 1: Reject the Null Hypothesis Conclusion
Suppose a biologist believes that a certain fertilizer will cause plants to grow more during a one-month period than they normally do, which is currently 20 inches. To test this, she applies the fertilizer to each of the plants in her laboratory for one month.
She then performs a hypothesis test at a 5% significance level using the following hypotheses:
- H 0 : μ = 20 inches (the fertilizer will have no effect on the mean plant growth)
- H A : μ > 20 inches (the fertilizer will cause mean plant growth to increase)
Suppose the p-value of the test turns out to be 0.002.
Here is how she would report the results of the hypothesis test:
We reject the null hypothesis at the 5% significance level. There is sufficient evidence to support the claim that this particular fertilizer causes plants to grow more during a one-month period than they normally do.
Example 2: Fail to Reject the Null Hypothesis Conclusion
Suppose the manager of a manufacturing plant wants to test whether or not some new method changes the number of defective widgets produced per month, which is currently 250. To test this, he measures the mean number of defective widgets produced before and after using the new method for one month.
He performs a hypothesis test at a 10% significance level using the following hypotheses:
- H 0 : μ after = μ before (the mean number of defective widgets is the same before and after using the new method)
- H A : μ after ≠ μ before (the mean number of defective widgets produced is different before and after using the new method)
Suppose the p-value of the test turns out to be 0.27.
Here is how he would report the results of the hypothesis test:
We fail to reject the null hypothesis at the 10% significance level. There is not sufficient evidence to support the claim that the new method leads to a change in the number of defective widgets produced per month.
Additional Resources
The following tutorials provide additional information about hypothesis testing:
Introduction to Hypothesis Testing 4 Examples of Hypothesis Testing in Real Life How to Write a Null Hypothesis
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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."
:max_bytes(150000):strip_icc():format(webp)/IMG_9791-89504ab694d54b66bbd72cb84ffb860e.jpg "is conclusion and hypothesis the same")
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.
:max_bytes(150000):strip_icc():format(webp)/VW-MIND-Amy-2b338105f1ee493f94d7e333e410fa76.jpg "is conclusion and hypothesis the same")
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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The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and their significance.
Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.
Importance of a Good Conclusion
A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:
- Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
- Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize your answer to the "So What?" question by placing the study within the context of how your research advances past research about the topic.
- Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
- Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
- Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.
Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.
Structure and Writing Style
I. General Rules
The general function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.
When writing the conclusion to your paper, follow these general rules:
- Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique, new, or crucial contributions your study made to the overall research about your topic?].
- Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
- Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further investigations should take place beyond the scope of your investigation.
Consider the following points to help ensure your conclusion is presented well:
- If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
- If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
- Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem].
The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.
II. Developing a Compelling Conclusion
Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:
- If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
- Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
- Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from your literature review].
- Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
- Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
- If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
- Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
- Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.
III. Problems to Avoid
Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .
Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].
Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.
Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.
Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].
Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader about the study's validity and realiability.
Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.
Writing Tip
Don't Belabor the Obvious!
Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.
Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.
Another Writing Tip
New Insight, Not New Information!
Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This why the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.
Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.
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What is the difference between a hypothesis and a conclusion?
And a conclusion is drawn AFTER the experiment is performed, and reports whether or not the results of the experiment supported the original hypothesis...
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How to write a strong conclusion for your research paper
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Writing a research paper is a chance to share your knowledge and hypothesis. It's an opportunity to demonstrate your many hours of research and prove your ability to write convincingly.
Ideally, by the end of your research paper, you'll have brought your readers on a journey to reach the conclusions you've pre-determined. However, if you don't stick the landing with a good conclusion, you'll risk losing your reader’s trust.
Writing a strong conclusion for your research paper involves a few important steps, including restating the thesis and summing up everything properly.
Find out what to include and what to avoid, so you can effectively demonstrate your understanding of the topic and prove your expertise.
- Why is a good conclusion important?
A good conclusion can cement your paper in the reader’s mind. Making a strong impression in your introduction can draw your readers in, but it's the conclusion that will inspire them.
- What to include in a research paper conclusion
There are a few specifics you should include in your research paper conclusion. Offer your readers some sense of urgency or consequence by pointing out why they should care about the topic you have covered. Discuss any common problems associated with your topic and provide suggestions as to how these problems can be solved or addressed.
The conclusion should include a restatement of your initial thesis. Thesis statements are strengthened after you’ve presented supporting evidence (as you will have done in the paper), so make a point to reintroduce it at the end.
Finally, recap the main points of your research paper, highlighting the key takeaways you want readers to remember. If you've made multiple points throughout the paper, refer to the ones with the strongest supporting evidence.
- Steps for writing a research paper conclusion
Many writers find the conclusion the most challenging part of any research project . By following these three steps, you'll be prepared to write a conclusion that is effective and concise.
- Step 1: Restate the problem
Always begin by restating the research problem in the conclusion of a research paper. This serves to remind the reader of your hypothesis and refresh them on the main point of the paper.
When restating the problem, take care to avoid using exactly the same words you employed earlier in the paper.
- Step 2: Sum up the paper
After you've restated the problem, sum up the paper by revealing your overall findings. The method for this differs slightly, depending on whether you're crafting an argumentative paper or an empirical paper.
Argumentative paper: Restate your thesis and arguments
Argumentative papers involve introducing a thesis statement early on. In crafting the conclusion for an argumentative paper, always restate the thesis, outlining the way you've developed it throughout the entire paper.
It might be appropriate to mention any counterarguments in the conclusion, so you can demonstrate how your thesis is correct or how the data best supports your main points.
Empirical paper: Summarize research findings
Empirical papers break down a series of research questions. In your conclusion, discuss the findings your research revealed, including any information that surprised you.
Be clear about the conclusions you reached, and explain whether or not you expected to arrive at these particular ones.
- Step 3: Discuss the implications of your research
Argumentative papers and empirical papers also differ in this part of a research paper conclusion. Here are some tips on crafting conclusions for argumentative and empirical papers.
Argumentative paper: Powerful closing statement
In an argumentative paper, you'll have spent a great deal of time expressing the opinions you formed after doing a significant amount of research. Make a strong closing statement in your argumentative paper's conclusion to share the significance of your work.
You can outline the next steps through a bold call to action, or restate how powerful your ideas turned out to be.
Empirical paper: Directions for future research
Empirical papers are broader in scope. They usually cover a variety of aspects and can include several points of view.
To write a good conclusion for an empirical paper, suggest the type of research that could be done in the future, including methods for further investigation or outlining ways other researchers might proceed.
If you feel your research had any limitations, even if they were outside your control, you could mention these in your conclusion.
After you finish outlining your conclusion, ask someone to read it and offer feedback. In any research project you're especially close to, it can be hard to identify problem areas. Having a close friend or someone whose opinion you value read the research paper and provide honest feedback can be invaluable. Take note of any suggested edits and consider incorporating them into your paper if they make sense.
- Things to avoid in a research paper conclusion
Keep these aspects to avoid in mind as you're writing your conclusion and refer to them after you've created an outline.
Dry summary
Writing a memorable, succinct conclusion is arguably more important than a strong introduction. Take care to avoid just rephrasing your main points, and don't fall into the trap of repeating dry facts or citations.
You can provide a new perspective for your readers to think about or contextualize your research. Either way, make the conclusion vibrant and interesting, rather than a rote recitation of your research paper’s highlights.
Clichéd or generic phrasing
Your research paper conclusion should feel fresh and inspiring. Avoid generic phrases like "to sum up" or "in conclusion." These phrases tend to be overused, especially in an academic context and might turn your readers off.
The conclusion also isn't the time to introduce colloquial phrases or informal language. Retain a professional, confident tone consistent throughout your paper’s conclusion so it feels exciting and bold.
New data or evidence
While you should present strong data throughout your paper, the conclusion isn't the place to introduce new evidence. This is because readers are engaged in actively learning as they read through the body of your paper.
By the time they reach the conclusion, they will have formed an opinion one way or the other (hopefully in your favor!). Introducing new evidence in the conclusion will only serve to surprise or frustrate your reader.
Ignoring contradictory evidence
If your research reveals contradictory evidence, don't ignore it in the conclusion. This will damage your credibility as an expert and might even serve to highlight the contradictions.
Be as transparent as possible and admit to any shortcomings in your research, but don't dwell on them for too long.
Ambiguous or unclear resolutions
The point of a research paper conclusion is to provide closure and bring all your ideas together. You should wrap up any arguments you introduced in the paper and tie up any loose ends, while demonstrating why your research and data are strong.
Use direct language in your conclusion and avoid ambiguity. Even if some of the data and sources you cite are inconclusive or contradictory, note this in your conclusion to come across as confident and trustworthy.
- Examples of research paper conclusions
Your research paper should provide a compelling close to the paper as a whole, highlighting your research and hard work. While the conclusion should represent your unique style, these examples offer a starting point:
Ultimately, the data we examined all point to the same conclusion: Encouraging a good work-life balance improves employee productivity and benefits the company overall. The research suggests that when employees feel their personal lives are valued and respected by their employers, they are more likely to be productive when at work. In addition, company turnover tends to be reduced when employees have a balance between their personal and professional lives. While additional research is required to establish ways companies can support employees in creating a stronger work-life balance, it's clear the need is there.
Social media is a primary method of communication among young people. As we've seen in the data presented, most young people in high school use a variety of social media applications at least every hour, including Instagram and Facebook. While social media is an avenue for connection with peers, research increasingly suggests that social media use correlates with body image issues. Young girls with lower self-esteem tend to use social media more often than those who don't log onto social media apps every day. As new applications continue to gain popularity, and as more high school students are given smartphones, more research will be required to measure the effects of prolonged social media use.
What are the different kinds of research paper conclusions?
There are no formal types of research paper conclusions. Ultimately, the conclusion depends on the outline of your paper and the type of research you’re presenting. While some experts note that research papers can end with a new perspective or commentary, most papers should conclude with a combination of both. The most important aspect of a good research paper conclusion is that it accurately represents the body of the paper.
Can I present new arguments in my research paper conclusion?
Research paper conclusions are not the place to introduce new data or arguments. The body of your paper is where you should share research and insights, where the reader is actively absorbing the content. By the time a reader reaches the conclusion of the research paper, they should have formed their opinion. Introducing new arguments in the conclusion can take a reader by surprise, and not in a positive way. It might also serve to frustrate readers.
How long should a research paper conclusion be?
There's no set length for a research paper conclusion. However, it's a good idea not to run on too long, since conclusions are supposed to be succinct. A good rule of thumb is to keep your conclusion around 5 to 10 percent of the paper's total length. If your paper is 10 pages, try to keep your conclusion under one page.
What should I include in a research paper conclusion?
A good research paper conclusion should always include a sense of urgency, so the reader can see how and why the topic should matter to them. You can also note some recommended actions to help fix the problem and some obstacles they might encounter. A conclusion should also remind the reader of the thesis statement, along with the main points you covered in the paper. At the end of the conclusion, add a powerful closing statement that helps cement the paper in the mind of the reader.
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- How to Write Discussions and Conclusions
The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.
What makes an effective discussion?
When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.
A successful discussion section puts your findings in context. It should include:
- the results of your research,
- a discussion of related research, and
- a comparison between your results and initial hypothesis.
Tip: Not all journals share the same naming conventions.
You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.
Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts.
Questions to ask yourself:
- Was my hypothesis correct?
- If my hypothesis is partially correct or entirely different, what can be learned from the results?
- How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic?
- Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies?
- How can future research build on these observations? What are the key experiments that must be done?
- What is the “take-home” message you want your reader to leave with?
How to structure a discussion
Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:
Writing Tips
While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results!
- Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations.
- Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion.
- Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research.
- State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons?
- Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions.
- If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided.
- Be concise. Adding unnecessary detail can distract from the main findings.
Don’t
- Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion.
- Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper.
- Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution.
- Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design.
- Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research.
Snippets of Effective Discussions:
Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach
Identifying reliable indicators of fitness in polar bears
- How to Write a Great Title
- How to Write an Abstract
- How to Write Your Methods
- How to Report Statistics
- How to Edit Your Work
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Are Research Questions and Hypotheses the Same?
3-minute read
- 23rd March 2022
A researcher might assume that research questions and hypotheses are identical concepts and should be treated equally in their approach to research. Are they really the same? Let’s find out!
While both are powerful research instruments that are determined in the initial experimental phase and help to guide the research planning and processes, the similarities end there. Read on to discover the differences between these two terms and understand how to accurately apply them in your research paper .
A hypothesis , specifically in academic research, is an educated guess or assumption about an expected relationship or occurrence that can be tested to determine if it’s correct. Essentially, you’ll make a statement —almost like a prediction—about a specific event or a relationship between two or more variables. You’ll then perform in-depth research into the topic and conduct experiments and tests to prove if the statement is true. A hypothesis is far more structured and requires you to have a fair amount of existing knowledge about your chosen topic. Using what you already know, you’ll follow a predetermined plan to prove or disprove your initial assumption.
Research Question
A research question is simply an unanswered question the researcher has about a topic that intrigues them or a query about the world or life in general. You’ll pose this question at the start of your research paper. You’ll then accumulate as much information as possible to determine a reasonable answer. Alternatively, with adequate proof, you can explain why the question should be left as is—unanswered. As you can see, research questions offer a more flexible approach since it’s essentially an investigation to appease your curiosity as a researcher. You don’t have to arrive at any specific answer, but your research should provide your readers with enough knowledge to draw their own conclusions.
At a Glance
● Hypotheses are used in mathematics, engineering, and every branch of science.
● Research questions are typically used when researching less calculable fields like literature, education, and sociology.
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● Prior knowledge is required to form a hypothesis, following a very structured approach to arrive at a definite answer—was the assumption correct or not?
● Researchers have more leniency when compiling papers based on research questions since the nature of the questions is more open-ended.
● For a hypothesis, your conclusion should state whether you were able to prove your hypothesis to be true or not based on the results of your research and testing.
● With a research question, you’ll use the conclusion section to summarize your answer based on your personal findings.
Now that you understand the correct way to incorporate these terms in your research papers, consider submitting a free sample to us ! Our proofreaders are available 24/7 to help ensure that your hard work translates into a concise, error-free, and effective academic achievement.
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AP®︎/College Statistics
Course: ap®︎/college statistics > unit 10.
- Idea behind hypothesis testing
- Examples of null and alternative hypotheses
- Writing null and alternative hypotheses
- P-values and significance tests
- Comparing P-values to different significance levels
- Estimating a P-value from a simulation
- Estimating P-values from simulations
Using P-values to make conclusions
- (Choice A) Fail to reject H 0 A Fail to reject H 0
- (Choice B) Reject H 0 and accept H a B Reject H 0 and accept H a
- (Choice C) Accept H 0 C Accept H 0
- (Choice A) The evidence suggests that these subjects can do better than guessing when identifying the bottled water. A The evidence suggests that these subjects can do better than guessing when identifying the bottled water.
- (Choice B) We don't have enough evidence to say that these subjects can do better than guessing when identifying the bottled water. B We don't have enough evidence to say that these subjects can do better than guessing when identifying the bottled water.
- (Choice C) The evidence suggests that these subjects were simply guessing when identifying the bottled water. C The evidence suggests that these subjects were simply guessing when identifying the bottled water.
- (Choice A) She would have rejected H a . A She would have rejected H a .
- (Choice B) She would have accepted H 0 . B She would have accepted H 0 .
- (Choice C) She would have rejected H 0 and accepted H a . C She would have rejected H 0 and accepted H a .
- (Choice D) She would have reached the same conclusion using either α = 0.05 or α = 0.10 . D She would have reached the same conclusion using either α = 0.05 or α = 0.10 .
- (Choice A) The evidence suggests that these bags are being filled with a mean amount that is different than 7.4 kg . A The evidence suggests that these bags are being filled with a mean amount that is different than 7.4 kg .
- (Choice B) We don't have enough evidence to say that these bags are being filled with a mean amount that is different than 7.4 kg . B We don't have enough evidence to say that these bags are being filled with a mean amount that is different than 7.4 kg .
- (Choice C) The evidence suggests that these bags are being filled with a mean amount of 7.4 kg . C The evidence suggests that these bags are being filled with a mean amount of 7.4 kg .
- (Choice A) They would have rejected H a . A They would have rejected H a .
- (Choice B) They would have accepted H 0 . B They would have accepted H 0 .
- (Choice C) They would have failed to reject H 0 . C They would have failed to reject H 0 .
- (Choice D) They would have reached the same conclusion using either α = 0.05 or α = 0.01 . D They would have reached the same conclusion using either α = 0.05 or α = 0.01 .
Ethics and the significance level α
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6.6 - confidence intervals & hypothesis testing.
Confidence intervals and hypothesis tests are similar in that they are both inferential methods that rely on an approximated sampling distribution. Confidence intervals use data from a sample to estimate a population parameter. Hypothesis tests use data from a sample to test a specified hypothesis. Hypothesis testing requires that we have a hypothesized parameter.
The simulation methods used to construct bootstrap distributions and randomization distributions are similar. One primary difference is a bootstrap distribution is centered on the observed sample statistic while a randomization distribution is centered on the value in the null hypothesis.
In Lesson 4, we learned confidence intervals contain a range of reasonable estimates of the population parameter. All of the confidence intervals we constructed in this course were two-tailed. These two-tailed confidence intervals go hand-in-hand with the two-tailed hypothesis tests we learned in Lesson 5. The conclusion drawn from a two-tailed confidence interval is usually the same as the conclusion drawn from a two-tailed hypothesis test. In other words, if the the 95% confidence interval contains the hypothesized parameter, then a hypothesis test at the 0.05 \(\alpha\) level will almost always fail to reject the null hypothesis. If the 95% confidence interval does not contain the hypothesize parameter, then a hypothesis test at the 0.05 \(\alpha\) level will almost always reject the null hypothesis.
Example: Mean Section
This example uses the Body Temperature dataset built in to StatKey for constructing a bootstrap confidence interval and conducting a randomization test .
Let's start by constructing a 95% confidence interval using the percentile method in StatKey:
The 95% confidence interval for the mean body temperature in the population is [98.044, 98.474].
Now, what if we want to know if there is enough evidence that the mean body temperature is different from 98.6 degrees? We can conduct a hypothesis test. Because 98.6 is not contained within the 95% confidence interval, it is not a reasonable estimate of the population mean. We should expect to have a p value less than 0.05 and to reject the null hypothesis.
\(H_0: \mu=98.6\)
\(H_a: \mu \ne 98.6\)
\(p = 2*0.00080=0.00160\)
\(p \leq 0.05\), reject the null hypothesis
There is evidence that the population mean is different from 98.6 degrees.
Selecting the Appropriate Procedure Section
The decision of whether to use a confidence interval or a hypothesis test depends on the research question. If we want to estimate a population parameter, we use a confidence interval. If we are given a specific population parameter (i.e., hypothesized value), and want to determine the likelihood that a population with that parameter would produce a sample as different as our sample, we use a hypothesis test. Below are a few examples of selecting the appropriate procedure.
Example: Cheese Consumption Section
Research question: How much cheese (in pounds) does an average American adult consume annually?
What is the appropriate inferential procedure?
Cheese consumption, in pounds, is a quantitative variable. We have one group: American adults. We are not given a specific value to test, so the appropriate procedure here is a confidence interval for a single mean .
Example: Age Section
Research question: Is the average age in the population of all STAT 200 students greater than 30 years?
There is one group: STAT 200 students. The variable of interest is age in years, which is quantitative. The research question includes a specific population parameter to test: 30 years. The appropriate procedure is a hypothesis test for a single mean .
Try it! Section
For each research question, identify the variables, the parameter of interest and decide on the the appropriate inferential procedure.
Research question: How strong is the correlation between height (in inches) and weight (in pounds) in American teenagers?
There are two variables of interest: (1) height in inches and (2) weight in pounds. Both are quantitative variables. The parameter of interest is the correlation between these two variables.
We are not given a specific correlation to test. We are being asked to estimate the strength of the correlation. The appropriate procedure here is a confidence interval for a correlation .
Research question: Are the majority of registered voters planning to vote in the next presidential election?
The parameter that is being tested here is a single proportion. We have one group: registered voters. "The majority" would be more than 50%, or p>0.50. This is a specific parameter that we are testing. The appropriate procedure here is a hypothesis test for a single proportion .
Research question: On average, are STAT 200 students younger than STAT 500 students?
We have two independent groups: STAT 200 students and STAT 500 students. We are comparing them in terms of average (i.e., mean) age.
If STAT 200 students are younger than STAT 500 students, that translates to \(\mu_{200}<\mu_{500}\) which is an alternative hypothesis. This could also be written as \(\mu_{200}-\mu_{500}<0\), where 0 is a specific population parameter that we are testing.
The appropriate procedure here is a hypothesis test for the difference in two means .
Research question: On average, how much taller are adult male giraffes compared to adult female giraffes?
There are two groups: males and females. The response variable is height, which is quantitative. We are not given a specific parameter to test, instead we are asked to estimate "how much" taller males are than females. The appropriate procedure is a confidence interval for the difference in two means .
Research question: Are STAT 500 students more likely than STAT 200 students to be employed full-time?
There are two independent groups: STAT 500 students and STAT 200 students. The response variable is full-time employment status which is categorical with two levels: yes/no.
If STAT 500 students are more likely than STAT 200 students to be employed full-time, that translates to \(p_{500}>p_{200}\) which is an alternative hypothesis. This could also be written as \(p_{500}-p_{200}>0\), where 0 is a specific parameter that we are testing. The appropriate procedure is a hypothesis test for the difference in two proportions.
Research question: Is there is a relationship between outdoor temperature (in Fahrenheit) and coffee sales (in cups per day)?
There are two variables here: (1) temperature in Fahrenheit and (2) cups of coffee sold in a day. Both variables are quantitative. The parameter of interest is the correlation between these two variables.
If there is a relationship between the variables, that means that the correlation is different from zero. This is a specific parameter that we are testing. The appropriate procedure is a hypothesis test for a correlation .
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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As nouns the difference between hypothesis and conclusion is that hypothesis is used loosely, a tentative conjecture explaining an observation, phenomenon or scientific problem that can be tested by further observation, investigation and/or experimentation. As a scientific term of art, see the attached quotation. Compare to theory, and quotation given there while conclusion is the end, finish ...
5. Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if…then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
The scientific method. At the core of biology and other sciences lies a problem-solving approach called the scientific method. The scientific method has five basic steps, plus one feedback step: Make an observation. Ask a question. Form a hypothesis, or testable explanation. Make a prediction based on the hypothesis.
H0: μafter = μbefore (the mean number of defective widgets is the same before and after using the new method) HA: μafter ≠ μbefore (the mean number of defective widgets produced is different before and after using the new method) Suppose the p-value of the test turns out to be 0.27. Here is how he would report the results of the ...
What is a Hypothesis? The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement, which is a brief summary of your research paper. The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion.
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 ...
The six steps of the scientific method include: 1) asking a question about something you observe, 2) doing background research to learn what is already known about the topic, 3) constructing a hypothesis, 4) experimenting to test the hypothesis, 5) analyzing the data from the experiment and drawing conclusions, and 6) communicating the results ...
scientific hypothesis, an idea that proposes a tentative explanation about a phenomenon or a narrow set of phenomena observed in the natural world.The two primary features of a scientific hypothesis are falsifiability and testability, which are reflected in an "If…then" statement summarizing the idea and in the ability to be supported or refuted through observation and experimentation.
Table of contents. Step 1: Restate the problem. Step 2: Sum up the paper. Step 3: Discuss the implications. Research paper conclusion examples. Frequently asked questions about research paper conclusions.
The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research.
The hypothesis of Andreas Cellarius, showing the planetary motions in eccentric and epicyclical orbits.. A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon.For a hypothesis to be a scientific hypothesis, the scientific method requires that one can test it. Scientists generally base scientific hypotheses on previous observations that cannot satisfactorily be explained ...
Well, an hypothesis is something that is proposed.... And the mark of a good hypothesis is its testability. That is there exist a few simple experiments whose results would confirm or deny the original hypothesis. And a conclusion is drawn AFTER the experiment is performed, and reports whether or not the results of the experiment supported the ...
Step 1: Restate the problem. Always begin by restating the research problem in the conclusion of a research paper. This serves to remind the reader of your hypothesis and refresh them on the main point of the paper. When restating the problem, take care to avoid using exactly the same words you employed earlier in the paper.
Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and ...
Hypothesis. A hypothesis, specifically in academic research, is an educated guess or assumption about an expected relationship or occurrence that can be tested to determine if it's correct. Essentially, you'll make a statement —almost like a prediction—about a specific event or a relationship between two or more variables.
Step 1: Answer your research question. Step 2: Summarize and reflect on your research. Step 3: Make future recommendations. Step 4: Emphasize your contributions to your field. Step 5: Wrap up your thesis or dissertation. Full conclusion example. Conclusion checklist. Other interesting articles.
A logical statement A statement that allows drawing a conclusion or result based on a hypothesis or premise. is a statement that, when true, allows us to take a known set of facts and infer (or assume) a new fact from them. Logical statements have two parts: The hypothesis The part of a logical statement that provides the premise on which the conclusion is based.
Onward! We use p -values to make conclusions in significance testing. More specifically, we compare the p -value to a significance level α to make conclusions about our hypotheses. If the p -value is lower than the significance level we chose, then we reject the null hypothesis H 0 in favor of the alternative hypothesis H a .
Theory vs. Hypothesis: Basics of the Scientific Method. Written by MasterClass. Last updated: Jun 7, 2021 • 2 min read. Though you may hear the terms "theory" and "hypothesis" used interchangeably, these two scientific terms have drastically different meanings in the world of science.
The conclusion drawn from a two-tailed confidence interval is usually the same as the conclusion drawn from a two-tailed hypothesis test. In other words, if the the 95% confidence interval contains the hypothesized parameter, then a hypothesis test at the 0.05 \(\alpha\) level will almost always fail to reject the null hypothesis.
Read the companion post for this one: How Hypothesis Tests Work: Significance Levels (Alpha) and P-values.In that post, I use the same graphical approach to illustrate why we need hypothesis tests, how significance levels and P-values can determine whether a result is statistically significant, and what that actually means.
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.
In a thesis or dissertation, the discussion is an in-depth exploration of the results, going into detail about the meaning of your findings and citing relevant sources to put them in context. The conclusion is more shorter and more general: it concisely answers your main research question and makes recommendations based on your overall findings.