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• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1. Ask a question

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2. Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.

Step 3. Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

4. Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

5. 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.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

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The Scientific Method

What is the scientific method, research starters, observation, analyze results, draw conclusions.

• Scientific Method Resources

According to Kosso (2011), the scientific method is a specific step-by-step method that aims to answer a question or prove a hypothesis.  It is the process used among all scientific disciplines and is used to conduct both small and large experiments.  It has been used for centuries to solve scientific problems and identify solutions.  While the terminology can be different across disciplines, the scientific method follows these six steps (Larson, 2015):

• Analyze results
• Draw conclusions

Click on each link to learn more about each step in the scientific method, or watch the video below for an introduction to each step.

Research Starters  is a feature available when searching  DragonQuest . You may notice when you enter a generic search term into DragonQuest that a research starter is your first result.

Research Starter  entries are similar to a Wikipedia entry of the topic, but  Research Starters  are pulled from quality sources such as Salem Press, Encyclopedia Britannica, and American National Biography.  Research Starters  can be a great place to begin your research, if you're not yet sure about your topic details.  There are several Research Starters related to the steps of the scientific method:

• Scientific method
• Research methodology
• Research methods

Using Research Starters

To use  Research Starters,  click on the title just as you would for any other  DragonQuest  entry. You will then find a broad overview of the topic. This entry is great for finding

• Subtopics that can narrow your searching
• Background information to support your claims
• Sources you can use and cite in your research

We do not recommend that you use  Research Starters  as a source itself though, because of the difficulties in citation.

Citing Research Starters

Using  Research Starters  as an actual source is not recommended.

Just as we do not recommend using Wikipedia as a source,  Research Starters  is the same. Use  Research Starters  as a starting point to get ideas about how to narrow your search and to use its bibliography to find sources you can cite.

We recommend this because citing  Research Starters  can be tricky as sometimes it will have insufficient bibliographic data to create your reference page.

To begin the scientific method, you have to observe something and identify a problem.  You can observe basically anything, such as a person, place, object, situation, or environment.  Examples of an observation include:

• "My cotton shirt gets more wet in the rain than my friend's silk shirt."
• "I feel more tired after eating a cookie than I do after eating a salad."

Once you have made an observation, it will lead to creating a scientific question (Larson, 2015).  The question focuses on a specific part of your observation:

• Why does a cotton shirt get more wet in the rain than a silk shirt?
• Why do I more tired after eating a cookie than if I ate a salad?

Scientific questions lead to research and crafting a hypothesis, which are the next steps in the scientific method.  Watch the video below for more information on observations.

Once you identify a topic and question from your observations, it is time to conduct some preliminary research.  It is meant to locate a potential answer to your research question or give you ideas on how to draft your hypothesis.  In some cases, it can also help you design an experiment once you determine your hypothesis.  It is a good idea to research your topic or problem using the library and/or the Internet.  It is also recommended to check out different source types for information, such as:

• Academic journals
• News reports
• Audiovisual media (radio, podcasts, etc.)

Background Information

It is important to gather lots of background information on your topic or problem so you understand the topic thoroughly.  It is also critical to find and understand what others have already written about your research question.  This prevents you from experimenting on an issue that already has a definitive answer.

If you need assistance in conducting preliminary research, view our guide on locating background information at the bottom of this box.

If you are unsure where you should start researching, you can view our list of science databases through our  A-Z database list  by selecting "Science" from the subjects dropdown menu.  We also have several research guides that cover topics in the sciences, which can be viewed on our Help page.

Not sure where to begin your research?  Try searching a database in our A-Z list or using one of our  EBSCOhost databases !

• Finding Background Information by Pfeiffer Library Last Updated Jul 10, 2024 78 views this year

When you have gathered enough information on your research question and determined that your question has not already been answered, you can form a hypothesis.  A hypothesis is an educated guess or possible explanation meant to answer your research question.  It often follows the "if, then..." sentence structure because it explains a cause/effect relationship between two variables.  A hypothesis is supposed to form a relationship between the two variables.

• Example hypothesis: "If I soak a penny in lemon juice, then it will look cleaner than if I soak it in soap."

In this example, it is explaining a relationship between a penny and different cleaning agents.  While crafting your hypothesis, it is important to make sure that your "then" statement is something that can be measured, either quantitatively or qualitatively.  In the above example, an experiment for the hypothesis would be measuring the cleanliness of the penny after being exposed to either soap or lemon juice.

For more information on hypotheses, view DragonQuest's Research Starter on hypotheses here .  Alternatively, you can watch the video below for more details on crafting hypotheses.

The fourth step in the scientific method is the experiment stage.  This is where you craft an experiment to test your hypothesis.  The point of an experiment is to find out how changing one thing impacts another (Larson, 2015).  To test a hypothesis, you must implement and change different variables in your experiment.

Anything that you modify in an experiment is considered a variable.  There are two types of variables:

• Independent variable:  The variable that is modified in an experiment so that is has a direct impact on the dependent variable.  It is the variable that you control in the experiment (Larson, 2015).
• Dependent variable:  The variable that is being tested in an experiment, whose measure is directly related to the change of the independent variable (the dependent variable is dependent on the independent variable).  This is what you measure to prove or disprove your hypothesis.

Every experiment must also have a control group , which is a variable that remains unchanged for the duration of the experiment (Larson, 2015).  It is used to compare the results of the dependent variable.  In the case of the sample hypothesis above, a control variable would be a penny that does not receive any cleaning agent.

Research Methods

There are several ways to conduct an experiment.  The approach you take is dependent on your own strengths and weaknesses, the nature of your topic/hypothesis, and the resources you have available to conduct the experiment.  If you are unsure as to what research method you would like to use for your experiment, you can view our research methodologies guide below.  DragonQuest also has a Research Starter on research methods, located  here .

• Research Methodologies by Pfeiffer Library Last Updated Aug 2, 2022 47289 views this year

When designing your experiment:

• Make a list of materials that you will need to conduct your experiment.  If you will need to purchase additional materials, create a budget.
• Consider the best locations for your experiment, especially if outside factors (weather, etc.) may effect the results.
• If you need additional funding for an experiment, it is recommended to consider writing a research proposal for the entity from which you want to receive funding.  You can view our guide on writing research proposals below.

You can also watch the video below to learn more about designing experiments.  Or, you can view DragonQuest's Research Starter on experiments here .

• Writing a Research Proposal by Pfeiffer Library Last Updated May 22, 2023 23606 views this year

When conducting your experiment:

• Record or write down your experimental procedure so that each variable it tested equally.  It is likely that you will conduct your experiment more than once, so it is important that it is conducted exactly the same each time (Larson, 2015).
• Be aware of outside factors that could impact your experiment and results.  Outside factors could include weather patterns, time of day, location, and temperature.
• Wear protective equipment to keep yourself safe during the experiment.
• Record your results on a transferrable platform (Google Spreadsheets, Microsoft Excel, etc.), especially if you plan on running statistical analyses on your data using a computer program.  You should also back your data up electronically so you do not lose it!
• Use a table or chart to record data by hand.  The x-axis (row) of a chart should represent the independent variable, while the y-axis (column) should represent the dependent variable (Riverside Local Schools, n.d.).
• Be prepared for unexpected results.  Some experiments can unexpectedly "go wrong" resulting in different data than planned.  Do not feel defeated if this happens in your experiment!  Once the tests are completed, you can analyze and determine why the experiment went differently.

Before arriving at a conclusion, you must look at all your evidence and analyze it.  Data analysis is "the process of interpreting the meaning of the data we have collected, organized, and displayed in the form of a chart or graph" (Riverside Local Schools, p. 1.).  If you did not create a graph or chart while recording your data, you may choose to create one to analyze your results.  Or, you may choose to create a more elaborate chart from the one you used in the experiment.  Graphs and charts organize data so that you can easily identify trends or patterns.  Patterns are similarities, differences, and relationships that tell you the "big picture" of an experiment (Riverside Local Schools, n.d.).

Questions to Consider

There are several things to consider when analyzing your data:

• What exactly am I trying to discover from this data?
• How does my data relate to my hypothesis?
• Are there any noticeable patterns or trends in the data?  If so, what do these patterns mean?
• Is my data good quality?  Was my data skewed in any way?
• Were there any limitations to retrieving this data during the experiment?

Once you have identified patterns or trends and considered the above questions, you can summarize your findings to draw your final conclusions.

Drawing conclusions is the final step in the scientific method.  It gives you the opportunity to combine your findings and communicate them to your audience.  A conclusion is "a summary of what you have learned from the experiment" (Riverside Local Schools, p. 1).  To draw a conclusion, you will compare your data analysis to your hypothesis and make a statement based on the comparison.  Your conclusion should answer the following questions:

• Was your hypothesis correct?
• Does my data support my hypothesis?
• If your hypothesis was incorrect, what did you learn from the experiment?
• Do you need to change a variable if the experiment is repeated?
• Is your data coherent and easy to understand?
• If the experiment failed, what did you learn?

A strong conclusion should also (American Psychological Association, 2021):

• Be justifiable by the data you collected.
• Provide generalizations that are limited to the sample you studied.
• Relate your preliminary research (background information) to your experiment and state how your conclusion is relevant.
• Be logical and address any potential discrepancies (American Psychological Association, 2021).

Reporting Your Results

Once you have drawn your conclusions, you will communicate your results to others.  This can be in the form of a formal research paper, presentation, or assignment that you submit to an instructor for a grade.  If you are looking to submit an original work to an academic journal, it will require approval and undergo peer-review before being published.  However, it is important to be aware of predatory publishers.  You can view our guide on predatory publishing below.

• Predatory Publishing by Pfeiffer Library Last Updated Aug 2, 2023 632 views this year
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• Last Updated: May 16, 2024 4:20 PM
• URL: https://library.tiffin.edu/thescientificmethod

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• Science Writing

How to Write an Effective Conclusion for a Science Lab Report

Last Updated: August 9, 2024 Fact Checked

• Discussing the Experiment
• Writing What You Learned
• Ending Your Conclusion

Finalizing Your Lab Report

This article was co-authored by Bess Ruff, MA . Bess Ruff is a Geography PhD student at Florida State University. She received her MA in Environmental Science and Management from the University of California, Santa Barbara in 2016. She has conducted survey work for marine spatial planning projects in the Caribbean and provided research support as a graduate fellow for the Sustainable Fisheries Group. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 1,770,606 times.

A lab report describes an entire experiment from start to finish, outlining the procedures, reporting results, and analyzing data. The report is used to demonstrate what has been learned, and it will provide a way for other people to see your process for the experiment and understand how you arrived at your conclusions. The conclusion is an integral part of the report; this is the section that reiterates the experiment’s main findings and gives the reader an overview of the lab trial. Writing a solid conclusion to your lab report will demonstrate that you’ve effectively learned the objectives of your assignment.

How to Write a Lab Report Conclusion

• Restate the purpose of the experiment and your procedures.
• Describe the results or findings and if they support your hypothesis.
• Mention what you've learned from the experiment.
• Note any errors or uncertainties that could affect the results.
• Propose experiments for the future to gain more findings.

Outlining Your Conclusion

• Restate : Restate the lab experiment by describing the assignment.
• Explain : Explain the purpose of the lab experiment. What were you trying to figure out or discover? Talk briefly about the procedure you followed to complete the lab.
• Results : Explain your results. Confirm whether or not your hypothesis was supported by the results.
• Uncertainties : Account for uncertainties and errors. Explain, for example, if there were other circumstances beyond your control that might have impacted the experiment’s results.
• New : Discuss new questions or discoveries that emerged from the experiment.

• Your assignment may also have specific questions that need to be answered. Make sure you answer these fully and coherently in your conclusion.

Discussing the Experiment and Hypothesis

• If you tried the experiment more than once, describe the reasons for doing so. Discuss changes that you made in your procedures.
• Brainstorm ways to explain your results in more depth. Go back through your lab notes, paying particular attention to the results you observed. [3] X Trustworthy Source University of North Carolina Writing Center UNC's on-campus and online instructional service that provides assistance to students, faculty, and others during the writing process Go to source

• Start this section with wording such as, “The results showed that…”
• You don’t need to give the raw data here. Just summarize the main points, calculate averages, or give a range of data to give an overall picture to the reader.
• Make sure to explain whether or not any statistical analyses were significant, and to what degree, such as 1%, 5%, or 10%.

• Use simple language such as, “The results supported the hypothesis,” or “The results did not support the hypothesis.”

Demonstrating What You Have Learned

• If it’s not clear in your conclusion what you learned from the lab, start off by writing, “In this lab, I learned…” This will give the reader a heads up that you will be describing exactly what you learned.
• Add details about what you learned and how you learned it. Adding dimension to your learning outcomes will convince your reader that you did, in fact, learn from the lab. Give specifics about how you learned that molecules will act in a particular environment, for example.
• Describe how what you learned in the lab could be applied to a future experiment.

• On a new line, write the question in italics. On the next line, write the answer to the question in regular text.

• If your experiment did not achieve the objectives, explain or speculate why not.

Wrapping Up Your Conclusion

• If your experiment raised questions that your collected data can’t answer, discuss this here.

• Describe what is new or innovative about your research.
• This can often set you apart from your classmates, many of whom will just write up the barest of discussion and conclusion.

Community Q&A

• Ensure the language used is straightforward with specific details. Try not to drift off topic. Thanks Helpful 1 Not Helpful 0
• Once again, avoid using personal pronouns (I, myself, we, our group) in a lab report. The first-person point-of-view is often seen as subjective, whereas science is based on objectivity. Thanks Helpful 1 Not Helpful 0
• If you include figures or tables in your conclusion, be sure to include a brief caption or label so that the reader knows what the figures refer to. Also, discuss the figures briefly in the text of your report. Thanks Helpful 1 Not Helpful 0

• Take care with writing your lab report when working in a team setting. While the lab experiment may be a collaborative effort, your lab report is your own work. If you copy sections from someone else’s report, this will be considered plagiarism. Thanks Helpful 4 Not Helpful 0

You Might Also Like

• ↑ https://phoenixcollege.libguides.com/LabReportWriting/introduction
• ↑ https://www.education.vic.gov.au/school/teachers/teachingresources/discipline/english/literacy/Pages/puttingittogether.aspx
• ↑ https://writingcenter.unc.edu/tips-and-tools/brainstorming/
• ↑ https://advice.writing.utoronto.ca/types-of-writing/lab-report/
• ↑ http://www.socialresearchmethods.net/kb/hypothes.php
• ↑ https://libguides.usc.edu/writingguide/conclusion
• ↑ https://libguides.usc.edu/writingguide/introduction/researchproblem
• ↑ http://writingcenter.unc.edu/handouts/scientific-reports/
• ↑ https://phoenixcollege.libguides.com/LabReportWriting/labreportstyle
• ↑ https://writingcenter.unc.edu/tips-and-tools/editing-and-proofreading/

About This Article

To write a good lab conclusion in science, start with restating the lab experiment by describing the assignment. Next, explain what you were trying to discover or figure out by doing the experiment. Then, list your results and explain how they confirmed or did not confirm your hypothesis. Additionally, include any uncertainties, such as circumstances beyond your control that may have impacted the results. Finally, discuss any new questions or discoveries that emerged from the experiment. For more advice, including how to wrap up your lab report with a final statement, keep reading. Did this summary help you? Yes No

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Chapter 1: Scientific Inquiry

Back to chapter, the scientific method, previous video 1.2: levels of organization, next video 1.4: inductive reasoning.

The scientific method is a detailed, stepwise process for answering questions. For example, a scientist makes an observation that the slugs destroy some cabbages but not those near garlic.

Such observations lead to asking questions, "Could garlic be used to deter slugs from ruining a cabbage patch?" After formulating questions, the scientist can then develop hypotheses —potential explanations for the observations that lead to specific, testable predictions.

In this case, a hypothesis could be that garlic repels slugs, which predicts that cabbages surrounded by garlic powder will suffer less damage than the ones without it. 

The hypothesis is then tested through a series of experiments designed to eliminate hypotheses.

The experimental setup involves defining variables. An independent variable is an item that is being tested, in this case, garlic addition. The dependent variable describes the measurement used to determine the outcome, such as the number of slugs on the cabbages.

In addition, the slugs must be divided into groups, experimental and control. These groups are identical, except that the experimental group is exposed to garlic powder.

After data are collected and analyzed, conclusions are made, and results are communicated to other scientists.

The scientific method is a detailed, empirical problem-solving process used by biologists and other scientists. This iterative approach involves formulating a question based on observation, developing a testable potential explanation for the observation (called a hypothesis), making and testing predictions based on the hypothesis, and using the findings to create new hypotheses and predictions.

Generally, predictions are tested using carefully-designed experiments. Based on the outcome of these experiments, the original hypothesis may need to be refined, and new hypotheses and questions can be generated. Importantly, this illustrates that the scientific method is not a stepwise recipe. Instead, it is a continuous refinement and testing of ideas based on new observations, which is the crux of scientific inquiry.

Science is mutable and continuously changes as scientists learn more about the world, physical phenomena and how organisms interact with their environment. For this reason, scientists avoid claiming to ‘prove' a specific idea. Instead, they gather evidence that either supports or refutes a given hypothesis.

Making Observations and Formulating Hypotheses

A hypothesis is preceded by an initial observation, during which information is gathered by the senses (e.g., vision, hearing) or using scientific tools and instruments. This observation leads to a question that prompts the formation of an initial hypothesis, a (testable) possible answer to the question. For example, the observation that slugs eat some cabbage plants but not cabbage plants located near garlic may prompt the question: why do slugs selectively not eat cabbage plants near garlic? One possible hypothesis, or answer to this question, is that slugs have an aversion to garlic. Based on this hypothesis, one might predict that slugs will not eat cabbage plants surrounded by a ring of garlic powder.

A hypothesis should be falsifiable, meaning that there are ways to disprove it if it is untrue. In other words, a hypothesis should be testable. Scientists often articulate and explicitly test for the opposite of the hypothesis, which is called the null hypothesis. In this case, the null hypothesis is that slugs do not have an aversion to garlic. The null hypothesis would be supported if, contrary to the prediction, slugs eat cabbage plants that are surrounded by garlic powder.

Testing a Hypothesis

When possible, scientists test hypotheses using controlled experiments that include independent and dependent variables, as well as control and experimental groups.

An independent variable is an item expected to have an effect (e.g., the garlic powder used in the slug and cabbage experiment or treatment given in a clinical trial). Dependent variables are the measurements used to determine the outcome of an experiment. In the experiment with slugs, cabbages, and garlic, the number of slugs eating cabbages is the dependent variable. This number is expected to depend on the presence or absence of garlic powder rings around the cabbage plants.

Experiments require experimental and control groups. An experimental group is treated with or exposed to the independent variable (i.e., the manipulation or treatment). For example, in the garlic aversion experiment with slugs, the experimental group is a group of cabbage plants surrounded by a garlic powder ring. A control group is subject to the same conditions as the experimental group, with the exception of the independent variable. Control groups in this experiment might include a group of cabbage plants in the same area that is surrounded by a non-garlic powder ring (to control for powder aversion) and a group that is not surrounded by any particular substance (to control for cabbage aversion). It is essential to include a control group because, without one, it is unclear whether the outcome is the result of the treatment or manipulation.

Refining a Hypothesis

If the results of an experiment support the hypothesis, further experiments may be designed and carried out to provide support for the hypothesis. The hypothesis may also be refined and made more specific. For example, additional experiments could determine whether slugs also have an aversion to other plants of the Allium genus, like onions.

If the results do not support the hypothesis, then the original hypothesis may be modified based on the new observations. It is important to rule out potential problems with the experimental design before modifying the hypothesis. For example, if slugs demonstrate an aversion to both garlic and non-garlic powder, the experiment can be carried out again using fresh garlic instead of powdered garlic. If the slugs still exhibit no aversion to garlic, then the original hypothesis can be modified.

Communication

The results of the experiments should be communicated to other scientists and the public, regardless of whether the data support the original hypothesis. This information can guide the development of new hypotheses and experimental questions.

VanCleave's Science Fun

Your Guide to Science Projects, Fun Experiments, and Science Research

Scientific Method: Conclusion

By Janice VanCleave

A conclusion is a summary of the experiment.

For a cause-effect experiment, the conclusion should state the hypothesis and and tell whether the results of the experiment supported the hypothesis. If the results did not support your hypothesis, say so, and then add information about why this happened.

For Example:

If the cause-effect experiment has the following problem, hypothesis,data, and results, the conclusion might be stated as shown below:

How does amount of yellow coloring added to blue water affect the shade of green produced?

Hypothesis:

If the amount of yellow coloring is increased, then the green shade of the water increases.

Data: The chart is an example—-Is it correct?

( Challenge: Perform the experiment and let me know your results.)

Right or wrong, the data chart is used to write the results

As the amount of yellow is added to the blue water, the color changes to blue-green, which changes to green, and then to a yellow-green.

Conclusion:

My hypothesis for this investigation was, “If the amount of yellow coloring is increased, then the green shade of the water increases.” The results of the experiment did not totally support my hypothesis. The first three measurements of yellow supported my hypothesis that adding yellow to the blue solution would increase the production of a green solution. But, as more yellow was added, the solution’s color became more yellow.

Further Investigations–

Often the results of an experiment will bring up questions that lead to further investigations.

For examples of further investigation ideas for the cause-effect experiment used for this conclusion example, can be found in this book:

Great Science Project Ideas from Real Kids

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Scientific Method: Step 3: HYPOTHESIS

• Step 1: QUESTION
• Step 2: RESEARCH
• Step 3: HYPOTHESIS
• Step 4: EXPERIMENT
• Step 5: DATA
• Step 6: CONCLUSION

Step 3: State your hypothesis

Now it's time to state your hypothesis . The hypothesis is an educated guess as to what will happen during your experiment. 

The hypothesis is often written using the words "IF" and "THEN." For example, " If I do not study, then I will fail the test." The "if' and "then" statements reflect your independent and dependent variables . 

The hypothesis should relate back to your original question and must be testable .

A word about variables...

Your experiment will include variables to measure and to explain any cause and effect. Below you will find some useful links describing the different types of variables.

• "What are independent and dependent variables" NCES
• [VIDEO] Biology: Independent vs. Dependent Variables (Nucleus Medical Media) Video explaining independent and dependent variables, with examples.

Resource Links

• What is and How to Write a Good Hypothesis in Research? (Elsevier)
• Hypothesis brochure from Penn State/Berks

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Scientific Method

Reviewed by: BD Editors

The scientific method is a series of processes that people can use to gather knowledge about the world around them, improve that knowledge, and attempt to explain why and/or how things occur. This method involves making observations, forming questions, making hypotheses, doing an experiment, analyzing the data, and forming a conclusion. Every scientific experiment performed is an example of the scientific method in action, but it is also used by non-scientists in everyday situations.

Scientific Method Overview

The scientific method is a process of trying to get as close as possible to the  objective truth . However, part of the process is to constantly refine your conclusions, ask new questions, and continue the search for the rules of the universe. Through the scientific method, scientists are trying to uncover how the world works and discover the laws that make it function in that way. You can use the scientific method to find answers for almost any question, though the scientific method can yield conflicting evidence based on the method of experimentation. In other words, the scientific method is a very useful way to figure things out – though it must be used with caution and care!

Scientific Method Steps

The exact steps of the scientific method vary from source to source , but the general procedure is the same: acquiring knowledge through observation and testing.

Making an Observation

The first step of the scientific method is to make an observation about the world around you. Before hypotheses can be made or experiments can be done, one must first notice and think about some sort of phenomena occurring. The scientific method is used when one does not know why or how something is occurring and wants to uncover the answer. But, before you can form a question you must notice something puzzling in the first place.

Asking a Question

Next, one must ask a question based on their observations. Here are some examples of good questions:

• Why is this thing occurring?
• How is this thing occurring?
• Why or how does it happen this way?

Sometimes this step is listed first in the scientific method, with making an observation (and researching the phenomena in question) listed as second. In reality, both making observations and asking questions tend to happen around the same time.

One can see a confusing occurrence and immediately think, “why is it occurring?” When observations are being made and questions are being formed, it is important to do research to see if others have already answered the question or uncovered information that may help you shape your question. For example, if you find an answer to why something is occurring, you may want to go a step further and figure out how it occurs.

Forming a Hypothesis

A hypothesis is an educated guess to explain the phenomena occurring based on prior observations. It answers the question posed in the previous step. Hypotheses can be specific or more general depending on the question being asked, but all hypotheses must be testable by gathering evidence that can be measured. If a hypothesis is not testable, then it is impossible to perform an experiment to determine whether the hypothesis is supported by evidence.

Performing an Experiment

After forming a hypothesis, an experiment must be set up and performed to test the hypothesis. An experiment must have an independent variable (something that is manipulated by the person doing the experiment), and a dependent variable (the thing being measured which may be affected by the independent variable). All other variables must be controlled so that they do not affect the outcome. During an experiment, data is collected. Data is a set of values; it may be quantitative (e.g. measured in numbers) or qualitative (a description or generalization of the results).

For example, if you were to test the effect of sunlight on plant growth, the amount of light would be the independent variable (the thing you manipulate) and the height of the plants would be the dependent variable (the thing affected by the independent variable). Other factors such as air temperature, amount of water in the soil, and species of plant would have to be kept the same between all of the plants used in the experiment so that you could truly collect data on whether sunlight affects plant growth. The data that you would collect would be quantitative – since you would measure the height of the plant in numbers.

Analyzing Data

After performing an experiment and collecting data, one must analyze the data. Research experiments are usually analyzed with statistical software in order to determine relationships among the data. In the case of a simpler experiment, one could simply look at the data and see how they correlate with the change in the independent variable.

Forming a Conclusion

The last step of the scientific method is to form a conclusion. If the data support the hypothesis, then the hypothesis may be the explanation for the phenomena. However, multiple trials must be done to confirm the results, and it is also important to make sure that the sample size—the number of observations made—is big enough so that the data is not skewed by just a few observations.

If the data do not support the hypothesis, then more observations must be made, a new hypothesis is formed, and the scientific method is used all over again. When a conclusion is drawn, the research can be presented to others to inform them of the findings and receive input about the validity of the conclusion drawn from the research.

Scientific Method Examples

There are very many examples of the use of the scientific method throughout history because it is the basis for all scientific experiments. Scientists have been conducting experiments using the scientific method for hundreds of years.

One such example is Francesco Redi’s experiment on spontaneous generation. In the 17 th Century, when Redi lived, people commonly believed that living things could spontaneously arise from organic material. For example, people believed that maggots were created from meat that was left out to sit. Redi had an alternate hypothesis: that maggots were actually part of the fly life cycle!

He conducted an experiment by leaving four jars of meat out: some uncovered, some covered with muslin, and some sealed completely. Flies got into the uncovered jars and maggots appeared a short time later. The jars that were covered had maggots on the outer surface of the muslin, but not inside the jars. Sealed jars had absolutely no maggots whatsoever.

Redi was able to conclude that maggots did not spontaneously arise in meat. He further confirmed the results by collecting captured maggots and growing them into adult flies. This may seem like common sense today, but back then, people did not know as much about the world, and it is through experiments like these that people uncovered what is now common knowledge.

Scientists use the scientific method in their research, but it is also used by people who aren’t scientists in everyday life. Even if you were not consciously aware of it, you have used the scientific method many times when solving problems around you.

For example, say you are at home and a lightbulb goes out. Noticing that the lightbulb is out is an observation. You would then naturally question, “Why is the lightbulb out?” and come up with possible guesses, or hypotheses. For example, you may hypothesize that the bulb has burned out. Then you would perform a very small experiment in order to test your hypothesis; namely, you would replace the bulb and analyze the data (“Did the light come back on?”).

If the light turned back on, you would conclude that the lightbulb had, in fact, burned out. But if the light still did not work, you would come up with other hypotheses (“The socket doesn’t work”, “Part of the lamp is broken,” “The fuse went out”, etc.) and test those.

1. Which step of the scientific method comes immediately after making observations and asking a question?

2. A scientist is performing an experiment to determine if the amount of light that rodents are exposed to affects their sleep cycle. She places some rodents in a room with 12 hours of light and 12 hours of darkness, some in a room with 24-hour light, and some in 24-hour darkness. What is the independent variable in this experiment?

3. What is the last step of the scientific method?

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The Scientific Method Lesson Plan: Developing Hypotheses

Submitted by: charlie conway.

This is a lesson plan designed to be incorporated into a elementary or middle school general science class. Using BrainPOP and its resources, students will be introduced (or further exposed) to the steps necessary to undertake scientific experimentation leading (perhaps) to a Science Fair project. The Scientific Method is a core structure in learning about scientific inquiry, and although there are many variations of this set of procedures, they all usually have similar components. This lesson should take 45-60 minutes, with opportunities for extending the lesson further.

Students will:

• Students will use BrainPOP features to build their understandings of the Scientific Method.
• Students will learn how to identify and write effective hypotheses.
• Students will use game play to write an appropriate hypothesis for an experiment.
• Students will identify and utilize the tools necessary to design a scientific investigation.
• Laptops/Computers
• Interactive White Board
• Pencil/Paper
• Class set of photocopies of the Scientific Method Flow Chart
• BrainPOP accounts (optional)

Vocabulary:

Preparation:.

These procedures may be modified according to the needs/resources of each teacher & class. For example, you may decide to do the quiz with pencil/paper, or do the quiz as a class.

Lesson Procedure:

• Ask the students how scientists answer questions and solve problems. Take a few minutes to explore students' prior knowledge with a short discussion.
• Tell the class that you're going to watch a BrainPOP movie about answering a scientific question about plant growth.
• Show the BrainPOP movie on the Scientific Method two times. The first time, students should just watch and listen. The second time they should take notes. Pause the movie at critical STOP points.
• Students should log on to their individual student accounts and take the Scientific Method Quiz to give the teacher some immediate feedback. (This can also be done as a pre-assessment, or at the very end of the lesson). NOTE: If you choose to, you can give a pencil/paper quiz also; students who work best with electronic media can be given accommodations). If you don't have access to individual student logins via MyBrainPOP (a school subscription), students can take the Review Quiz or paper quiz instead.
• Discuss the main points from the movie: a. Write the definition of the scientific method: the procedure scientists use to help explain why things happen. b. Make a list on the board of the steps mentioned as part of the scientific method: problem, fact finding, observation, inference, hypothesis, experiment, conclusions. c. Tell students that there are various versions of the scientific method that they may see, but they are all basically the same.
• Hand out the Scientific Method Flow Chart . Introduce the "If...then...because..." format for writing hypotheses. Give the students 10 minutes to complete the sheet with their group. They may use their notes from the movie to help them, and/or work collaboratively with other students.
• Discuss some of the student responses in class. Focus on the hypotheses, and explain that a good hypothesis is a testable explanation of the problem. For example, a good hypothesis to the third problem would be, "If I move farther away from the microwave oven, then the cell phone signal will improve because I am further away from the source of interference." Show how this is a TESTABLE hypothesis that can lead to a scientific experiment.
• Introduce the students to the Pavlov’s Dog game in GameUP. Allow time for the kids to explore the game without telling them why they are playing it.
• After 10-15 minutes, have the students take a break from playing, and have a short discussion about the game. Ask if anyone was able to complete the task successfully, and have them share how they got the "diploma." If time allows, show the students how to complete the task so that they all understand that the dog has been conditioned to respond to a stimulus (noise before food has been introduced).
• Have the students write a hypothesis that Pavlov may have written before he started his experiment. Students can either do this with pencil/paper, or the teacher may create a BrainPOP quiz and have students submit their hypothesis electronically. This may be used as a part of the assessment.
• Choose some sample responses from the students, highlighting the hypotheses that are TESTABLE, and not just guesses or predictions.

If this lesson is an introduction to allowing students to plan and carry out their own experiments, then all that follows is naturally an extension to the lesson.

Other, shorter extensions are easy to develop as well.

Extension Activities:

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1.1.2 Scientific Methods

• Post author By Hemant More
• Post date October 15, 2019
• No Comments on 1.1.2 Scientific Methods

Science > Physics > Scientific Methods

At the core, all sciences lie a problem-solving approach called the scientific method. It is a set of procedures that scientists follow in order to gain knowledge about the world. It is a process for experimentation that is used to explore observations and answer questions. It doesn’t mean that every scientist uses exactly the same procedure.  When direct experimentation is not possible, scientists modify the method. Even when modified, the goal remains the same: to discover cause and effect relationships by asking questions, carefully gathering and examining the evidence, and seeing if all the available information can be combined into a logical answer. Collecting lots of data without being able to find any basic underlying principles is not science. Let us discuss scientific methods.

List of Sub-Topics:

• 1.1.2.1 Introduction
• 1.1.2.2.1 Make an Observation
• 1.1.2.2.2 Ask Question
• 1.1.2.2.3 Form Hypothesis
• 1.1.2.2.4 Do Experimentation
• 1.1.2.2.5 Test Predictions
• 1.1.2.2.6 Make Analysis
• 1.1.2.2.7 Arrive at Conclusion
• 1.1.2.2.8 Iteration of Process (if Required)
• 1.1.2.2.9 Report Results
• 1.1.2.2.10 Peer Review
• 1.1.2.3 Replacing Old Hypothesis
• 1.1.2.4 Concept Application

A theory established with the help of twenty facts must explain thirty, and lead to the discovery of ten more.” – Jean Baptiste Andre Dumas

Scientific theories are created to explain the results of experiments that were created under certain conditions. A successful theory will also make new predictions about new experiments under new conditions. Thus the scientific method is an iterative process because after finding the conclusion, the scientist may come up with a new hypothesis.

Back to List of Sub-Topics

1.1.2.2 Elements of Scientific Methods:

The scientific method has following steps, plus one feedback step:

1.1.2.2.1 Make an Observation:

Observation is a fundamental and crucial element in the scientific method for several reasons.  The process begins with the observation of a phenomenon or an event in the natural world. This could be a question about why something happens or a curiosity about a particular occurrence.

Kinds of Observations:

Observations in scientific research can be classified into two main types: subjective and objective. These distinctions are based on the degree of personal bias and interpretation involved in the observation process.

Objective Observation:

Objective observations are those that are based on factual and measurable data, free from personal bias or interpretation. These observations are often quantifiable, and different observers should be able to arrive at the same or similar results when using the same criteria. Objective observations are considered more reliable and are crucial for establishing the empirical foundation of scientific inquiry. Examples of objective observations include measurements, counts, and recordings of physical properties. When Newton was sitting below an apple tree, he saw apple falling down. His observation was that anything released from height always falls back on the earth. It was objective observation and any other person had observed it.

Example: Measuring the temperature of a substance using a thermometer.

Subjective Observation:

Subjective observations are influenced by personal opinions, biases, or interpretations. They are more dependent on the observer’s perspective and may vary from one individual to another. Subjective observations are often qualitative in nature and involve the observer’s feelings, impressions, or judgments. While subjective observations can provide valuable insights, they are inherently more prone to variability and may be less reliable than objective observations.

Example: Describing the color of a sunset using words like “vibrant” or “mellow.”

It’s important to note that both objective and subjective observations have their place in scientific research, and the key is to be aware of the nature of the observation and its potential impact on the results. In many scientific investigations, a combination of both types of observations is used to obtain a comprehensive understanding of a phenomenon. For example: The statement that the room temperature is 15 o C is objective observation while there is cold in a room is subjective observation.

Researchers often strive to minimize subjectivity by employing standardized measurement tools, clear criteria, and systematic procedures. Additionally, the use of statistical analysis can help quantify and control for variability in both types of observations.

Thus, objective observations are based on measurable and quantifiable data, while subjective observations involve personal interpretations and may vary among individuals. The careful consideration of both types of observations contributes to a well-rounded and robust scientific understanding of the natural world.

Importance of observation:

Observation is a fundamental and crucial element in the scientific method for several reasons. Here are some of the key importance of observation:

• Initiating the Scientific Process: Observations serve as the starting point for scientific inquiry. Scientists often notice interesting patterns, phenomena, or anomalies in the natural world that spark their curiosity and lead to the formulation of questions.
• Formulating Questions: Observations help scientists formulate specific and testable questions about the natural world. These questions guide the scientific investigation by providing a focus and direction for research.
• Generating Hypotheses: By carefully observing and analyzing patterns or behaviors, scientists can generate hypotheses – educated guesses or potential explanations for the observed phenomena. Hypotheses are then tested through experimentation.
• Guiding Experimentation: Observations guide the design of experiments or the collection of data. Scientists use their initial observations to develop predictions and design experiments that will test the validity of their hypotheses.
• Providing Baseline Information: Before conducting experiments, scientists often need to establish a baseline by observing and recording the natural state of the phenomenon they are studying. This baseline is essential for making meaningful comparisons with the experimental results.
• Identifying Variables: Through observation, scientists identify and understand the relevant variables that may influence the phenomenon under investigation. This knowledge is crucial for designing experiments with controlled conditions.
• Detecting Anomalies or Patterns: Observations may reveal unexpected patterns or anomalies in the data. These unexpected findings can lead to new hypotheses or prompt scientists to reevaluate existing theories, contributing to the advancement of knowledge.
• Building a Foundation for Theory: Observations, when systematically collected and analyzed, contribute to the accumulation of evidence that supports or challenges scientific theories. Theories are overarching explanations that integrate and generalize observations and hypotheses.
• Inspiring Further Research: Observations often inspire additional research questions and investigations. New observations can arise during the course of experimentation, leading to a cycle of continuous inquiry and discovery.
• Applying Scientific Knowledge: Observations are not limited to the early stages of the scientific method. They play a role throughout the process, helping scientists interpret results, refine hypotheses, and apply their findings to real-world situations.

Thus, observation is integral to the scientific method as it provides the initial impetus for scientific inquiry, guides the formulation of questions and hypotheses, and shapes the entire process of experimentation and analysis. It is through careful and systematic observation that scientists gain insights into the workings of the natural world and contribute to the advancement of scientific knowledge.

1.1.2.2.2 Ask a question:

The next step in the scientific method is to ask a question about the scientific observation made in the first step. Frame questions using What, When, Who, Which, Why, Where and How. The questions should be well conceived and should be such that it leads to the next step of development of hypothesis. Gather information and give objective answers to the questions framed. Mistakes of past should be avoided in this step.

Based on observations, scientists formulate a clear and specific question that they want to answer. This question should be testable and lead to a hypothesis. The importance of formulating a clear and well-defined question in the scientific method cannot be overstated.

Importance of Questions:

Questions serve as the starting point for scientific inquiry, and they play several critical roles in the research process as follows:

• Guiding the Research Process: A well-formulated question provides direction and purpose for the scientific investigation. It helps researchers focus their efforts and resources on addressing a specific aspect of the natural world.
• Defining the Scope of the Study: The question helps define the boundaries of the study by specifying what is being investigated and what is not. This clarity is essential for designing experiments, collecting data, and drawing meaningful conclusions.
• Formulating Hypotheses: Questions lead to the formulation of hypotheses, which are testable and falsifiable predictions about the outcome of the research. Hypotheses provide a framework for designing experiments and guiding data collection.
• Setting Objectives: Research questions help researchers establish clear objectives for their study. These objectives outline what the researchers aim to achieve and guide the development of the research plan.
• Inspiring Curiosity: Questions often arise from observations or existing knowledge gaps, sparking curiosity and interest in understanding a particular phenomenon. This curiosity is a driving force behind scientific exploration and discovery.
• Facilitating Communication: A well-constructed research question is crucial for effectively communicating the purpose and focus of the study to other researchers, stakeholders, and the broader scientific community.
• Promoting Relevance and Significance: Questions help researchers evaluate the relevance and significance of their work. A clearly defined question ensures that the study addresses an important issue or contributes to existing knowledge in a meaningful way.
• Aiding in Experimental Design: The research question guides the design of experiments and the selection of appropriate methods. It helps researchers identify the variables to be measured and controlled, ensuring a systematic and rigorous approach to data collection.
• Evaluating Success and Progress: Research questions provide criteria for evaluating the success and progress of the study. The answers to these questions, obtained through experimentation and analysis, determine the overall success of the research.
• Facilitating Replication and Extension: A well-formulated question facilitates the replication of studies by providing a clear framework for other researchers to follow. It also sets the stage for future research by identifying areas for further investigation and extension.

^hus, the formulation of a clear and focused research question is foundational to the scientific method. It provides direction, structure, and purpose to the research process, guiding the development of hypotheses, experimental design, and data analysis. A well-constructed question is essential for generating meaningful and reliable scientific knowledge.

1.1.2.2.3 Form the Hypothesis:

Scientists use their knowledge of past events to develop a general principle or explanation to help predict future events. The general principle is called a hypothesis. The type of reasoning involved is called inductive reasoning (deriving a generalization from specific details). Thus a hypothesis is an educated guess about how things work. It is a testable explanation. It is a potential answer to the question at hand. The scientist predicts what the outcome will be when he or she tests the hypothesis. When a hypothesis involves a cause-and-effect relationship, we state our hypothesis to indicate there is no effect. A hypothesis, which asserts no effect, is called a null hypothesis.

The hypothesis should be of the form “If _____[I do this] _____, then _____[this]_____ will happen.”

Characteristics of Hypothesis:

• It should be a general principle that holds across space and time
• It should be a tentative idea
• It should agree with available observations
• It should be kept as simple as possible.
• It should be testable and potentially falsifiable. In other words, there should be a way to show the hypothesis is false; a way to disprove the hypothesis.

Importance of Hypothesis:

The hypothesis is a critical component of the scientific method and holds significant importance in the research process. Here are several reasons why hypotheses are essential in scientific methods:

• Testable Predictions: A hypothesis provides a testable statement or prediction about the relationship between variables. This allows researchers to design experiments or gather data to determine whether the prediction is supported or refuted.
• Guidance for Research Design: The hypothesis guides the design of the research study, helping researchers determine what variables to measure, how to manipulate them, and what methods to use. It provides a roadmap for the entire research process.
• Focusing the Investigation: The hypothesis focuses the investigation on a specific aspect of the natural world. It helps researchers narrow down their research question and avoid unnecessary or irrelevant information.
• Formulating Research Objectives: Hypotheses help researchers set clear objectives for their study. These objectives outline the specific goals of the research and provide a basis for evaluating the success of the investigation.
• Systematic and Rigorous Approach: The formulation of a hypothesis encourages a systematic and rigorous approach to scientific inquiry. Researchers structure their experiments and data collection methods to test the hypothesis in a controlled and replicable manner.
• Organizing Information: Hypotheses serve as a framework for organizing information. They provide a structure for interpreting and analyzing data, helping researchers make sense of their observations in the context of the proposed explanation.
• Facilitating Communication: Clearly stated hypotheses facilitate communication among researchers. They convey the purpose and expectations of the study, allowing other scientists to understand, critique, and build upon the research.
• Testing and Refining Theories: Hypotheses contribute to the testing and refinement of scientific theories. By subjecting hypotheses to empirical scrutiny, scientists gather evidence that either supports or challenges existing theories, leading to a deeper understanding of natural phenomena.
• Generating New Questions: Even if a hypothesis is not supported, the process of testing it can generate new questions and avenues for further research. This iterative process is fundamental to the dynamic nature of scientific inquiry.
• Enhancing Objectivity: Formulating a hypothesis encourages objectivity in the research process. It requires researchers to make explicit predictions that can be objectively tested, helping to minimize personal biases and subjective interpretations.

Thus, hypotheses are crucial in scientific methods because they guide the research process, facilitate the formulation of testable predictions, and contribute to the systematic and organized nature of scientific inquiry. They provide a framework for designing experiments, interpreting results, and advancing our understanding of the natural world

1.1.2.2.4 Do Experimentation:

Experimentation is a fundamental component of the scientific method, playing a crucial role in testing hypotheses and advancing scientific knowledge. Scientists conduct experiments or make observations to gather data that will either support or refute the hypothesis. Experiments are designed to be controlled and repeatable, allowing for the testing of specific variables. Systematic and careful collection of data during the experiment is crucial. This involves recording observations, measurements, and any other relevant information that can be analyzed later.

The primary purpose of experimentation is to test hypotheses. A hypothesis is a testable and falsifiable prediction about the relationship between variables. Through experimentation, scientists gather empirical evidence to either support or refute their hypotheses. Results from experiments may lead to the refinement or revision of hypotheses. If the data do not support the initial hypothesis, scientists may need to reconsider their assumptions and develop new hypotheses for further testing.

Experiments involve manipulating one or more variables while keeping other factors constant. This control over conditions helps isolate the effects of the variable(s) being tested, allowing researchers to draw meaningful conclusions. Experiments should be designed in a way that allows other researchers to replicate the study and obtain similar results. Reproducibility is a cornerstone of the scientific method, as it helps validate the reliability and generalizability of findings.

Experimentation relies on empirical observation—direct, systematic observation or measurement of phenomena.  It generates quantifiable data that can be analyzed statistically. This data-driven approach enhances objectivity and allows researchers to draw conclusions based on evidence rather than subjective interpretation. This empirical evidence forms the basis for drawing conclusions about the natural world.

Well-designed experiments are crucial for establishing cause-and-effect relationships between variables. By manipulating an independent variable and observing changes in a dependent variable, researchers can infer causal connections. Experimental design aims to minimize bias and ensure objectivity in the collection and interpretation of data. Randomization, blinding, and careful control of variables help reduce the influence of extraneous factors.

Experiments undergo critical evaluation during the peer review process. Other scientists assess the experimental design, methodology, and results to ensure the study’s validity and contribute to the quality assurance of scientific knowledge. Successful experimentation contributes to the advancement of scientific knowledge by providing new insights, confirming or challenging existing theories, and expanding our understanding of natural phenomena. The scientific method is often an iterative process, with experimentation leading to new questions, hypotheses, and subsequent experiments. This cycle of inquiry fosters continuous growth in scientific understanding.

Thus, experimentation is a cornerstone of the scientific method, providing a systematic and empirical approach to testing hypotheses, establishing causal relationships, and advancing our understanding of the natural world. Well-designed experiments contribute to the reliability and validity of scientific findings.

Importance of Experimentation:

Experimentation is a crucial and foundational component of the scientific method, and its importance lies in several key aspects:

• Testing Hypotheses: Experimentation allows scientists to test hypotheses by manipulating variables and observing the resulting changes. This empirical testing is essential for determining the validity and reliability of proposed explanations for natural phenomena.
• Empirical Validation: Through experimentation, scientists gather empirical evidence—observable and measurable data—providing a basis for making informed conclusions. This empirical validation distinguishes scientific inquiry from mere speculation. Experiments generate quantifiable data, which enhances objectivity and facilitates statistical analysis. The use of measurable outcomes allows for a rigorous evaluation of the significance of observed effects.
• Establishing Cause and Effect: Experiments involve creating controlled conditions to isolate specific variables. This control is crucial for accurately attributing observed changes to the manipulated factor, reducing the influence of confounding variables. Thus, well-designed experiments help establish cause-and-effect relationships between variables. By controlling conditions and systematically manipulating one variable while keeping others constant, researchers can infer causal connections.
• Reproducibility and Verification: The ability to reproduce experimental results is a hallmark of scientific reliability. Experiments should be designed to be replicable by other researchers, allowing for the independent verification of findings and strengthening the credibility of scientific knowledge.
• Iterative Nature of Science: Experiments contribute to the iterative nature of the scientific process. The results of one set of experiments can lead to new questions, hypotheses, and subsequent experiments, fostering a continuous cycle of inquiry and discovery.
• Refinement of Hypotheses: Experimentation often leads to the refinement or revision of hypotheses. If the results do not align with predictions, scientists may reconsider their initial assumptions, adjust their hypotheses, and design new experiments to further investigate.
• Problem Solving: Experiments help address specific questions or problems, providing a structured and systematic approach to problem-solving. This process allows researchers to investigate, analyze, and draw conclusions in a methodical manner.
• Advancing Scientific Knowledge: Successful experiments contribute to the advancement of scientific knowledge by providing insights, confirming or challenging existing theories, and expanding our understanding of the natural world. Each experiment adds to the cumulative body of scientific knowledge. Experimentation often leads to practical applications and technological innovations. Scientific discoveries made through experimentation can have real-world implications, influencing fields such as medicine, technology, and environmental science.
• Peer Review and External Validation: Experiments undergo scrutiny through the peer review process. Other experts in the field evaluate the experimental design, methodology, and results, ensuring the rigor and validity of the research.

Thus, experimentation is vital to the scientific method as it provides a systematic, empirical, and objective approach to testing hypotheses, establishing causal relationships, and advancing our understanding of the natural world. It is a cornerstone of scientific inquiry and contributes to the reliability and credibility of scientific knowledge.

1.1.2.2.5 Test the Predictions:

To test hypothesis experiments are performed. This helps in making a decision whether the prediction of the hypothesis is accurate. Observation during the experiment is a statement of knowledge gained through the senses or through the use of scientific equipment. Observations are crucial for collecting data.  All the conditions that are subject to change during the experiment are called variables.  Conduct a fair test (controlled experiment) by making sure that only one factor is changed at a time while keeping all other conditions the same. The experiment should be such that it can be reproduced by anyone wanting to test the hypothesis. It means anyone with the necessary skills and equipment should be able to get the same results from the same experiment. The experiment should be repeated several times.

Importance of Prediction:

Predictions play a crucial role in the scientific method, contributing to the formulation and testing of hypotheses. Here are several reasons highlighting the importance of predictions in scientific methods:

• Testability: Predictions make hypotheses testable. A hypothesis becomes more meaningful and scientifically relevant when it can be translated into specific predictions that can be empirically tested through observation or experimentation.
• Guiding Experimental Design: Predictions guide the design of experiments by specifying the expected outcomes or patterns. They help researchers determine the variables to measure, manipulate, or control, ensuring a systematic and focused approach to data collection.
• Objective Criteria for Evaluation: Predictions provide objective criteria for evaluating the success or failure of a hypothesis. The comparison between predicted and observed outcomes allows researchers to assess the validity of their ideas and draw meaningful conclusions.
• Formulating Hypotheses: Predictions are often integral to the formulation of hypotheses. A hypothesis typically includes an explanation (the hypothesis itself) and a prediction about what will happen under certain conditions. This combination guides the research process.
• Communication of Expectations: Predictions communicate researchers’ expectations to others in the scientific community. Clear predictions make it easier for peers to understand the hypothesis being tested and to replicate or challenge the research.
• Establishing Baseline Expectations: Predictions help establish baseline expectations for a study. By stating what is anticipated based on the hypothesis, researchers provide a benchmark against which actual observations or experimental results can be compared.
• Increasing Objectivity: Predictions contribute to objectivity in scientific research. They encourage researchers to define expected outcomes in advance, reducing the potential for bias in the interpretation of results.
• Refining and Revising Hypotheses: The process of testing predictions may lead to the refinement or revision of hypotheses. If predictions are not supported by the data, researchers may need to reconsider their initial assumptions and modify their hypotheses accordingly.
• Generating New Knowledge: Predictions, whether confirmed or refuted, contribute to the generation of new knowledge. Successful predictions support the hypothesis and add to the body of established scientific understanding, while unexpected results can prompt further inquiry and exploration.
• Fostering Accountability: Making explicit predictions holds researchers accountable for their ideas. It encourages transparency in the scientific process, allowing others to scrutinize the research and contributing to the credibility and reliability of scientific findings.

Thus, predictions are vital in scientific methods as they make hypotheses testable, guide experimental design, and provide objective criteria for evaluating research outcomes. They enhance communication, objectivity, and accountability in scientific inquiry, contributing to the advancement of knowledge and the refinement of scientific theories.

1.1.2.2.6 Make Analysis:

The collected data is analyzed to determine whether the results support or contradict the hypothesis. Statistical methods are often used to assess the significance of the findings. Once the results of experiment are in, the scientist must begin the analysis of the data. Data analysis involves comparing the results of the experiment to the prediction posed by the hypothesis.  Based on the observations he or she made, the scientist has to determine whether the hypothesis was correct.

Importance of Analysis:

Analysis is a critical step in the scientific method, and its importance cannot be overstated. Once data has been collected through experiments or observations, analysis is performed to draw meaningful conclusions and derive scientific insights. Here are several reasons highlighting the importance of analysis in scientific methods:

• Interpretation of Data: Analysis allows researchers to interpret the raw data collected during experiments or observations. It involves organizing, summarizing, and presenting the data in a way that facilitates understanding.
• Identification of Patterns and Trends: Through analysis, researchers can identify patterns, trends, and relationships within the data. This helps in recognizing consistent observations and determining whether these patterns support or refute the initial hypothesis.
• Statistical Significance: Statistical analysis is often employed to assess the significance of the observed results. Statistical tests help researchers determine whether the differences or patterns observed in the data are likely to be due to chance or if they are statistically significant.
• Validation of Hypotheses: The analysis is a crucial step in testing hypotheses. By comparing the observed data to the predicted outcomes (based on the hypothesis), researchers can assess the validity of their hypotheses and draw conclusions about the relationships between variables.
• Drawing Conclusions: Analysis allows researchers to draw conclusions from the data. Conclusions may include whether the hypothesis is supported, whether there are unexpected findings, and what implications the results have for the broader scientific understanding.
• Quality Control: Analysis serves as a form of quality control by helping researchers identify errors, outliers, or anomalies in the data. This ensures the reliability and accuracy of the results.
• Informing Further Research: The insights gained from analysis can inform future research directions. Whether the results support or challenge existing theories, the analysis contributes to the collective knowledge and may suggest avenues for further exploration.
• Communication of Findings: Analysis is essential for communicating research findings to the scientific community and the public. Clear and well-documented analysis ensures that others can understand, evaluate, and build upon the research.
• Peer Review: In the peer review process, other experts in the field critically evaluate the analysis conducted by researchers. This external scrutiny helps ensure the robustness and validity of the scientific findings.
• Integration with Existing Knowledge: Analysis allows researchers to integrate their findings with existing scientific knowledge. This integration is essential for advancing understanding within a particular field.

Thus, analysis is a crucial step in the scientific method because it transforms raw data into meaningful information, enables the testing of hypotheses, supports informed decision-making, and contributes to the broader scientific knowledge base.

1.1.2.2.7 Arrive at Conclusion:

The conclusion in scientific methods represents the final stage of the research process where researchers summarize their findings, interpret the results, and draw overarching insights from the study.  Based on the analysis, scientists draw conclusions regarding the validity of the hypothesis. If the hypothesis is supported by the evidence, it may be considered a valid explanation. If not, the scientist may need to revise the hypothesis and repeat the process.

• Summarizing Results: The conclusion begins by summarizing the results obtained from the experimentation or observational study. This includes a concise presentation of the data collected and any patterns or trends observed.
• Comparison with Predictions: Researchers compare the observed results with the predictions made based on the initial hypotheses. This step is crucial for determining whether the hypotheses were supported, contradicted, or require modification.
• Addressing Objectives: The conclusion revisits the objectives set at the beginning of the study, assessing whether the research goals were met. This provides a clear overview of the study’s purpose and the extent to which it was successful.
• Interpretation of Findings: Researchers interpret the findings in the context of existing knowledge and theories. This involves explaining the significance of the results, identifying any unexpected outcomes, and providing insights into the underlying mechanisms.
• Discussion of Limitations: The conclusion acknowledges any limitations or constraints in the study. This transparency is essential for recognizing the boundaries of the research and understanding the potential impact on the generalizability of the results.
• Implications for Future Research: Researchers often discuss the implications of their findings for future research. This includes identifying unanswered questions, proposing new avenues of inquiry, and suggesting areas where further investigation is warranted.
• Practical Applications: If applicable, the conclusion may discuss the practical applications of the research. This addresses how the findings could be translated into real-world solutions or contribute to advancements in technology, medicine, or other fields.
• Drawing Generalizations: The conclusion involves drawing generalizations based on the study’s results. This step assesses the broader significance of the findings and their potential contribution to the scientific understanding of the studied phenomenon.
• Reflection on Hypotheses: Researchers reflect on the hypotheses formulated at the outset of the study. They assess whether the experimental results support or refute the hypotheses and consider any modifications needed based on the observed data.
• Contributions to Scientific Knowledge: The conclusion articulates how the study contributes to the existing body of scientific knowledge. This could involve confirming or challenging established theories, providing new insights, or addressing gaps in current understanding.
• Final Remarks: The conclusion often concludes with final remarks summarizing the key findings and emphasizing the significance of the research. This section may also discuss the broader implications of the study for the field.

The conclusion is a critical part of the scientific method as it consolidates the entire research process, provides closure to the study, and communicates the key findings and their implications to the scientific community and beyond. It serves as a bridge between the data collected and the broader understanding of the natural world.

1.1.2.2.8 Iteration of Process (if Required):

The conclusion of a scientific process is a statement of whether the original hypothesis was supported or refuted by the observations gathered. From the analysis of the experiment, there are two possible outcomes: the results agree with the prediction or they disagree with the prediction. If results agree with predictions, the hypothesis is accepted. If the results do not agree with the predictions, the hypothesis is rejected. If scientist find the results are not as per their prediction, they communicate the results of their experiment and then go back and construct a new hypothesis and prediction based on the information they learned during their experiment. This starts much of the process of the scientific method over again. Even if they find that their hypothesis was supported, they may want to test it again with a better hypothesis. Thus the process can iterated.

It is to be noted that the results that support a hypothesis can’t conclusively prove that it’s correct, but they do mean it’s likely to be correct. On the other hand, if results contradict a hypothesis, that hypothesis is probably not correct. Thus hypothesis should be testable and potentially falsifiable

1.1.2.2.9 Report the Result:

Scientists communicate their findings through publications, presentations, or other means. This allows other researchers to scrutinize the work, replicate experiments, and build upon the knowledge gained.

Any accepted hypothesis must be communicated to the scientific community in a final report form. It is a very important element of scientific methods. Scientists publish their findings in scientific journals and books, in talks at national and international meetings and in seminars at colleges and universities. It allows other people to verify the results, develop new tests of the hypothesis or apply the knowledge gained during experiments to solve other problems.

1.1.2.2.10 Peer Review:

Peer review is a critical and integral component of the scientific method. It is a process by which research articles, studies, and findings are evaluated by experts in the same field before they are published in scientific journals or presented at conferences.

• Quality Assurance: Peer review serves as a mechanism for quality assurance in scientific research. Experts evaluate the methodology, experimental design, data analysis, and interpretations to ensure that the research meets rigorous scientific standards.
• Validation of Research Findings: Peer review helps validate the credibility and reliability of research findings. When a study undergoes peer review and is accepted for publication, it implies that knowledgeable experts have deemed the research sound and worthy of dissemination.
• Identification of Flaws and Errors: Peers critically assess the study for potential flaws, errors, or weaknesses in the experimental design, methodology, or analysis. This process aids in identifying and addressing any limitations in the research.
• Improving Clarity and Communication: Peer reviewers provide feedback on the clarity and coherence of the research manuscript. This feedback can lead to improvements in how the study is presented, making it more understandable and accessible to the broader scientific community.
• Ethical Considerations: Peer review helps ensure that research adheres to ethical standards. Reviewers assess the ethical treatment of human or animal subjects, proper citation of sources, and the avoidance of plagiarism or other unethical practices.
• Contribution to Scientific Discourse: Peer-reviewed publications contribute to the ongoing scientific discourse. By providing a platform for rigorous and validated research, peer-reviewed journals contribute to the accumulation of knowledge in a particular field.
• Verification of Results: Peers assess the validity of experimental results and the interpretation of data. This verification process is crucial for confirming the accuracy of the findings and preventing the dissemination of potentially misleading or flawed information.
• Feedback for Authors: Authors receive constructive feedback from peer reviewers, helping them refine and improve their work. This iterative process can lead to stronger research designs, more robust analyses, and clearer communication of results.
• Prevention of Pseudoscience: Peer review acts as a safeguard against the publication of pseudoscientific or unfounded claims. Rigorous evaluation by experts helps filter out studies that lack scientific merit, maintaining the integrity of the scientific literature.
• Establishing Scientific Consensus: Peer-reviewed articles contribute to the establishment of scientific consensus. When multiple studies undergo rigorous review and consistently support similar conclusions, it strengthens the credibility and acceptance of those findings within the scientific community.
• Credentialing and Recognition: Peer-reviewed publications are often considered a mark of credibility and expertise in a researcher’s career. Success in peer-reviewed journals can enhance a researcher’s reputation and contribute to their professional recognition.

Thus, peer review is a cornerstone of the scientific method, ensuring the quality, validity, and ethical integrity of scientific research. It plays a pivotal role in advancing knowledge, maintaining standards, and facilitating the dissemination of reliable information within the scientific community.

1.1.2.3 Examples of Replacement of Old Hypothesis:

It may happen that a new observation or a new measurement shows a discrepancy between existing theory and the observation. Then the theory is modified or even to be replaced by a new theory. This can be understood with the following examples.

• The old concept that the earth is flat is replaced by that the earth is a sphere by the observation of distant ships in the sea that first, we see the mast of the ship and then the whole ship.
• The concept of the earth is a perfect sphere is replaced by that the earth is oblate spheroid by the observation that the value of acceleration due to gravity varies as we move from the equator to the poles.
• The concept of a geocentric universe is replaced by the heliocentric universe by astronomical observations by Copernicus and Galileo.
• Newton’s corpuscular theory based on observation of shadows is replaced by Huygens’s wave theory of light on observation of diffraction and interference of light. Huygens’ wave theory is replaced by quantum theory n observation of photoelectric effect.
• Newton’s laws are not applicable to bodies moving with very high-speed comparable with light and hence to explain the behavior body at much higher speed the theory of relativity was proposed by Einstein.

1.1.2.4 Concept Application:

A psychic conducts seances in which the spirits of the dead speak to the participants. He says he has special psychic powers not possessed by other people, which allow him to “channel” the communications with the spirits. What part of the scientific method is being violated here?

According to the scientific method, any experiment should be reproducible. It means anyone with the necessary skills and equipment should be able to get the same results from the same experiment. If very few are able to perform the experiment, then it is not a scientific method.

Conclusion:

Scientific methods refer to systematic, empirical approaches used by scientists to investigate natural phenomena, answer questions, or test hypotheses. The scientific method typically involves a series of steps, though these steps may be adapted or varied depending on the specific field or nature of the research. It’s important to note that the scientific method is not always a linear process, and scientists may iterate through these steps multiple times, refining their hypotheses and experimental designs based on new information and insights. Additionally, the application of the scientific method can vary across different scientific disciplines.

Related Topics:

• 1.1.3 Scientific View
• 1.1.4 Physics and Other Sciences
• 1.1.1 What is physics?

For More Topics in Physics Click Here

• Tags Accountability , Analysis , Cause and Effect , Empirical Validation , Evaluation , Experimental Design , Experimentation , External Validation , Hypotheses , Interpretation of Data , Investigation , Iterative Nature of Science , Objectives , Objectivity , Observation , Peer Review , Predictions , Problem Solving , Quality Assurance , Quality control , Question , Reproducibility , Research , Research Design , Research Objectives , Research Process , Scientific Knowledge , Scientific methods , Scientific Process , Scientific Theory , Statistical Significance , Subjective Observation , Testability , Verification

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Understanding Science

How science REALLY works...

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Correcting misconceptions.

Many students have misconceptions about what science is and how it works. This section explains and corrects some of the most common misconceptions that students are likely have trouble with. If you are interested in common misconceptions about  teaching  the nature and process of science, visit our page on that topic .

Jump to: Misinterpretations of the scientific process | Misunderstandings of the limits of science | Misleading stereotypes of scientists | Vocabulary mix-ups | Roadblocks to learning science

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Misinterpretations of the scientific process

Misconception: science is a collection of facts..

CORRECTION:

Because science classes sometimes revolve around dense textbooks, it’s easy to think that’s all there is to science: facts in a textbook. But that’s only part of the picture. Science  is  a body of knowledge that one can learn about in textbooks, but it is also a process. Science is an exciting and dynamic process for discovering how the world works and building that knowledge into powerful and coherent frameworks. To learn more about the process of science, visit our section on  How science works .

MISCONCEPTION: Science is complete.

Since much of what is taught in introductory science courses is knowledge that was constructed in the 19th and 20th centuries, it’s easy to think that science is finished — that we’ve already discovered most of what there is to know about the natural world . This is far from accurate. Science is an ongoing process, and there is much more yet to learn about the world. In fact, in science, making a key discovery often leads to many new questions ripe for investigation. Furthermore, scientists are constantly elaborating, refining, and revising established scientific ideas based on new evidence and perspectives. To learn more about this, visit our page describing how scientific ideas lead to ongoing research .

MISCONCEPTION: There is a single Scientific Method that all scientists follow.

“The Scientific Method” is often taught in science courses as a simple way to understand the basics of scientific testing. In fact, the Scientific Method represents how scientists usually write up the results of their studies (and how a few investigations are actually done), but it is a grossly oversimplified representation of how scientists generally build knowledge. The process of science is exciting, complex, and unpredictable. It involves many different people, engaged in many different activities, in many different orders. To review a more accurate representation of the process of science, explore our  flowchart .

MISCONCEPTION: The process of science is purely analytic and does not involve creativity.

Perhaps because the Scientific Method presents a linear and rigid representation of the process of science, many people think that doing science involves closely following a series of steps, with no room for creativity and inspiration. In fact, many scientists recognize that creative thinking is one of the most important skills they have — whether that creativity is used to come up with an alternative hypothesis, to devise a new way of testing an idea, or to look at old data in a new light. Creativity is critical to science!

MISCONCEPTION: When scientists analyze a problem, they must use either inductive or deductive reasoning.

Scientists use all sorts of different reasoning modes at different times — and sometimes at the same time — when analyzing a problem. They also use their creativity to come up with new ideas, explanations, and tests. This isn’t an either/or choice between induction and deduction. Scientific analysis often involves jumping back and forth among different modes of reasoning and creative brainstorming! What’s important about scientific reasoning is not what all the different modes of reasoning are called, but the fact that the process relies on careful, logical consideration of how evidence supports or does not support an idea, of how different scientific ideas are related to one another, and of what sorts of things we can expect to observe if a particular idea is true. If you are interested in learning about the difference between induction and deduction, visit our  FAQ on the topic .

MISCONCEPTION: Experiments are a necessary part of the scientific process. Without an experiment, a study is not rigorous or scientific.

Perhaps because the Scientific Method and popular portrayals of science emphasize  experiments , many people think that science can’t be done  without  an experiment. In fact, there are  many  ways to test almost any scientific idea; experimentation is only one approach. Some ideas are best tested by setting up a  controlled experiment  in a lab, some by making detailed observations of the natural world, and some with a combination of strategies. To study detailed examples of how scientific ideas can be tested fairly, with and without experiments, check out our side trip  Fair tests: A do-it-yourself guide .

MISCONCEPTION: "Hard" sciences are more rigorous and scientific than "soft" sciences.

Some scientists and philosophers have tried to draw a line between “hard” sciences (e.g., chemistry and physics) and “soft” ones (e.g., psychology and sociology). The thinking was that hard science used more rigorous, quantitative methods than soft science did and so were more trustworthy. In fact, the rigor of a scientific study has much more to do with the investigator’s approach than with the discipline. Many psychology studies, for example, are carefully controlled, rely on large sample sizes, and are highly quantitative. To learn more about how rigorous and fair tests are designed, regardless of discipline, check out our side trip  Fair tests: A do-it-yourself guide .

MISCONCEPTION: Scientific ideas are absolute and unchanging.

Because science textbooks change very little from year to year, it’s easy to imagine that scientific ideas don’t change at all. It’s true that some scientific ideas are so well established and supported by so many lines of evidence, they are unlikely to be completely overturned. However, even these established ideas are subject to modification based on new evidence and perspectives. Furthermore, at the cutting edge of scientific research — areas of knowledge that are difficult to represent in introductory textbooks — scientific ideas may change rapidly as scientists test out many different possible explanations trying to figure out which are the most accurate. To learn more about this, visit our page describing  how science aims to build knowledge .

MISCONCEPTION: Because scientific ideas are tentative and subject to change, they can't be trusted.

Especially when it comes to scientific findings about health and medicine, it can sometimes seem as though scientists are always changing their minds. One month the newspaper warns you away from chocolate’s saturated fat and sugar; the next month, chocolate companies are bragging about chocolate’s antioxidants and lack of trans-fats. There are several reasons for such apparent reversals. First, press coverage tends to draw particular attention to disagreements or ideas that conflict with past views. Second, ideas at the cutting edge of research (e.g., regarding new medical studies) may change rapidly as scientists test out many different possible explanations trying to figure out which are the most accurate. This is a normal and healthy part of the process of science. While it’s true that all scientific ideas are subject to change if warranted by the evidence, many scientific ideas (e.g., evolutionary theory, foundational ideas in chemistry) are supported by many lines of evidence, are extremely reliable, and are unlikely to change. To learn more about provisionality in science and its portrayal by the media, visit a section from our  Science Toolkit .

MISCONCEPTION: Scientists' observations directly tell them how things work (i.e., knowledge is "read off" nature, not built).

Because science relies on observation and because the process of science is unfamiliar to many, it may seem as though scientists build knowledge directly through observation. Observation  is  critical in science, but scientists often make  inferences  about what those observations mean. Observations are part of a complex process that involves coming up with ideas about how the natural world works and seeing if observations back those explanations up. Learning about the inner workings of the natural world is less like reading a book and more like writing a non-fiction book — trying out different ideas, rephrasing, running drafts by other people, and modifying text in order to present the clearest and most accurate explanations for what we observe in the natural world. To learn more about how scientific knowledge is built, visit our section  How science works .

MISCONCEPTION: Science proves ideas.

Journalists often write about “scientific proof” and some scientists talk about it, but in fact, the concept of proof — real, absolute proof — is not particularly scientific. Science is based on the principle that  any  idea, no matter how widely accepted today, could be overturned tomorrow if the evidence warranted it. Science accepts or rejects ideas based on the evidence; it does not prove or disprove them. To learn more about this, visit our page describing  how science aims to build knowledge .

MISCONCEPTION: Science can only disprove ideas.

This misconception is based on the idea of falsification, philosopher Karl Popper’s influential account of scientific justification, which suggests that all science can do is reject, or falsify, hypotheses — that science cannot find evidence that  supports  one idea over others. Falsification was a popular philosophical doctrine — especially with scientists — but it was soon recognized that falsification wasn’t a very complete or accurate picture of how scientific knowledge is built. In science, ideas can never be completely proved or completely disproved. Instead, science accepts or rejects ideas based on supporting and refuting evidence, and may revise those conclusions if warranted by new evidence or perspectives.

MISCONCEPTION: If evidence supports a hypothesis, it is upgraded to a theory. If the theory then garners even more support, it may be upgraded to a law.

This misconception may be reinforced by introductory science courses that treat hypotheses as “things we’re not sure about yet” and that only explore established and accepted theories. In fact, hypotheses, theories, and laws are rather like apples, oranges, and kumquats: one cannot grow into another, no matter how much fertilizer and water are offered. Hypotheses, theories, and laws are all scientific explanations that differ in breadth — not in level of support. Hypotheses are explanations that are limited in scope, applying to fairly narrow range of phenomena. The term  law  is sometimes used to refer to an idea about how observable phenomena are related — but the term is also used in other ways within science. Theories are deep explanations that apply to a broad range of phenomena and that may integrate many hypotheses and laws. To learn more about this, visit our page on  the different levels of explanation in science .

MISCONCEPTION: Scientific ideas are judged democratically based on popularity.

When newspapers make statements like, “most scientists agree that human activity is the culprit behind global warming,” it’s easy to imagine that scientists hold an annual caucus and vote for their favorite hypotheses. But of course, that’s not quite how it works. Scientific ideas are judged not by their popularity, but on the basis of the evidence supporting or contradicting them. A hypothesis or theory comes to be accepted by many scientists (usually over the course of several years — or decades!) once it has garnered many lines of supporting evidence and has stood up to the scrutiny of the scientific community. A hypothesis accepted by “most scientists,” may not be “liked” or have positive repercussions, but it is one that science has judged likely to be accurate based on the evidence. To learn more about  how science judges ideas , visit our series of pages on the topic in our section on how science works.

MISCONCEPTION: The job of a scientist is to find support for his or her hypotheses.

This misconception likely stems from introductory science labs, with their emphasis on getting the “right” answer and with congratulations handed out for having the “correct” hypothesis all along. In fact, science gains as much from figuring out which hypotheses are likely to be wrong as it does from figuring out which are supported by the evidence. Scientists may have personal favorite hypotheses, but they strive to consider multiple hypotheses and be unbiased when evaluating them against the evidence. A scientist who finds evidence contradicting a favorite hypothesis may be surprised and probably disappointed, but can rest easy knowing that he or she has made a valuable contribution to science.

MISCONCEPTION: Scientists are judged on the basis of how many correct hypotheses they propose (i.e., good scientists are the ones who are "right" most often).

The scientific community  does  value individuals who have good intuition and think up creative explanations that turn out to be correct — but it  also  values scientists who are able to think up creative ways to test a new idea (even if the test ends up contradicting the idea) and who spot the fatal flaw in a particular argument or test. In science, gathering evidence to determine the accuracy of an explanation is just as important as coming up with the explanation that winds up being supported by the evidence.

MISCONCEPTION: Investigations that don't reach a firm conclusion are useless and unpublishable.

Perhaps because the last step of the Scientific Method is usually “draw a conclusion,” it’s easy to imagine that studies that don’t reach a clear conclusion must not be scientific or important. In fact,  most  scientific studies don’t reach “firm” conclusions. Scientific articles usually end with a discussion of the limitations of the tests performed and the alternative hypotheses that might account for the phenomenon. That’s the nature of scientific knowledge — it’s inherently tentative and could be overturned if new evidence, new interpretations, or a better explanation come along. In science, studies that carefully analyze the strengths and weaknesses of the test performed and of the different alternative explanations are particularly valuable since they encourage others to more thoroughly scrutinize the ideas and evidence and to develop new ways to test the ideas. To learn more about publishing and scrutiny in science, visit our discussion of  peer review .

MISCONCEPTION: Scientists are completely objective in their evaluation of scientific ideas and evidence.

Scientists do strive to be unbiased as they consider different scientific ideas, but scientists are people too. They have different personal beliefs and goals — and may favor different hypotheses for different reasons. Individual scientists may not be completely objective, but science can overcome this hurdle through the action of the scientific community, which scrutinizes scientific work and helps balance biases. To learn more, visit  Scientific scrutiny  in our section on the social side of science.

MISCONCEPTION: Scientists' personal traits, experiences, emotions, and values don't factor into the process of science.

Scientists’ personal traits, experiences, emotions, and values influence their selection of research topic, hypotheses, chosen research methods, and interpretations of results and evidence, shaping the course of science in many ways. For example, a social scientist who has experienced poverty might be more likely to study this topic and might formulate different hypotheses about its causes than someone from a different background. Furthermore, experiencing curiosity and wonder is a key motivation for many scientists to pursue their work. Because science is a human endeavor, these fundamentally human traits (our unique identities, emotions, and values) play their role in the process. This means that scientists cannot be completely objective (see above). However, individual biases can be overcome through community scrutiny, helping science self-correct and continue to build more and more accurate explanations for how the world works.

MISCONCEPTION: Science is pure. Scientists work without considering the applications of their ideas.

It’s true that some scientific research is performed without any attention to its applications, but this is certainly not true of all science. Many scientists choose specific areas of research (e.g., malaria genetics) because of the practical ramifications new knowledge in these areas might have. And often, basic research that is performed without any aim toward potential applications later winds up being extremely useful. To learn about some of the many applications of scientific knowledge visit  What has science done for you lately?

Misunderstandings of the limits of science

Misconception: science contradicts the existence of god..

Because of some vocal individuals (both inside and outside of science) stridently declaring their beliefs, it’s easy to get the impression that science and religion are at war. In fact, people of many different faiths and levels of scientific expertise see no contradiction at all between science and religion. Because science deals only with  natural  phenomena and explanations, it cannot support or contradict the existence of  supernatural  entities — like God. To learn more, visit our side trip  Science and religion: Reconcilable differences .

MISCONCEPTION: Science and technology can solve all our problems.

The feats accomplished through the application of scientific knowledge are truly astounding. Science has helped us eradicate deadly diseases, communicate with people all over the world, and build  technologies  that make our lives easier everyday. But for all scientific innovations, the costs must be carefully weighed against the benefits. And, of course, there’s no guarantee that solutions for some problems (e.g., finding an HIV vaccine) exist — though science is likely to help us discover them if they do exist. Furthermore, some important human concerns (e.g. some spiritual and aesthetic questions) cannot be addressed by science at all. Science is a marvelous tool for helping us understand the natural world, but it is not a cure-all for whatever problems we encounter.

Misleading stereotypes of scientists

Misconception: science is a solitary pursuit..

When scientists are portrayed in movies and television shows, they are often ensconced in silent laboratories, alone with their bubbling test-tubes. This can make science seem isolating. In fact, many scientists work in busy labs or field stations, surrounded by other scientists and students. Scientists often collaborate on studies with one another, mentor less experienced scientists, and just chat about their work over coffee. Even the rare scientist who works entirely alone depends on interactions with the rest of the scientific community to scrutinize his or her work and get ideas for new studies. Science is a social endeavor. To learn more, visit our section on the  Social side of science .

MISCONCEPTION: Science is done by "old, white men."

While it is true that Western science used to be the domain of white males, this is no longer the case. The diversity of the scientific community is expanding rapidly. Science is open to anyone who is curious about the natural world and who wants to take a scientific approach to his or her investigations. To see how science benefits from a diverse community, visit  Diversity makes the difference .

MISCONCEPTION: Scientists are atheists.

This is far from true. A 2005 survey of scientists at top research universities found that more than 48% had a religious affiliation and that more than 75% believed that religions convey important truths. 1  Some scientists are not religious, but many others subscribe to a specific faith and/or believe in higher powers. Science itself is a secular pursuit, but welcomes participants from all religious faiths. To learn more, visit our side trip  Science and religion: Reconcilable differences .

Vocabulary mix-ups

Some misconceptions occur simply because scientific language and everyday language use some of the same words differently.

Facts  are statements that we know to be true through direct  observation . In everyday usage, facts are a highly valued form of knowledge because we can be so confident in them. Scientific thinking, however, recognizes that, though facts are important, we can only be completely confident about relatively simple statements. For example, it may be a fact that there are three trees in your backyard. However, our knowledge of how all trees are related to one another is not a fact; it is a complex body of knowledge based on many different  lines of evidence  and reasoning that may change as new  evidence  is discovered and as old evidence is interpreted in new ways. Though our knowledge of tree relationships is not a fact, it is broadly applicable, useful in many situations, and synthesizes many individual facts into a broader framework.  Science  values facts but recognizes that many forms of knowledge are more powerful than simple facts.

In everyday language, a  law  is a rule that must be abided or something that can be relied upon to occur in a particular situation. Scientific laws, on the other hand, are less rigid. They may have exceptions, and, like other scientific knowledge, may be modified or rejected based on new evidence and perspectives. In science, the term  law  usually refers to a generalization about  data  and is a compact way of describing what we’d expect to happen in a particular situation. Some laws are non-mechanistic statements about the relationship among observable phenomena. For example, the ideal gas law describes how the pressure, volume, and temperature of a particular amount of gas are related to one another. It does not describe how gases  must  behave; we know that gases do not precisely conform to the ideal gas law. Other laws deal with phenomena that are not directly observable. For example, the second law of thermodynamics deals with entropy, which is not directly observable in the same way that volume and pressure are. Still other laws offer more mechanistic explanations of phenomena. For example, Mendel’s first law offers a  model  of how genes are distributed to gametes and offspring that helps us make  predictions  about the outcomes of genetic crosses. The term  law  may be used to describe many different forms of scientific knowledge, and whether or not a particular idea is called a law has much to do with its discipline and the time period in which it was first developed.

Observation

In everyday language, the word  observation  generally means something that we’ve seen with our own eyes. In science, the term is used more broadly. Scientific observations can be made directly with our own senses or may be made indirectly through the use of tools like thermometers, pH test kits, Geiger counters, etc. We can’t actually  see  beta particles, but we can observe them using a Geiger counter. To learn more about the role of observation in science, visit  Observation beyond our eyes  in our section on how science works.

In everyday language, the word  hypothesis  usually refers to an educated guess — or an idea that we are quite uncertain about. Scientific hypotheses, however, are much more informed than any guess and are usually based on prior experience, scientific background knowledge, preliminary observations, and logic. In addition, hypotheses are often supported by many different lines of evidence — in which case, scientists are more confident in them than they would be in any mere “guess.” To further complicate matters, science textbooks frequently misuse the term in a slightly different way. They may ask students to make a  hypothesis  about the outcome of an experiment (e.g., table salt will dissolve in water more quickly than rock salt will). This is simply a prediction or a guess (even if a well-informed one) about the outcome of an experiment. Scientific hypotheses, on the other hand, have explanatory power — they are explanations for phenomena. The idea that table salt dissolves faster than rock salt is not very hypothesis-like because it is not very explanatory. A more scientific (i.e., more explanatory) hypothesis might be “The amount of surface area a substance has affects how quickly it can dissolve. More surface area means a faster rate of dissolution.” This hypothesis has some explanatory power — it gives us an idea of  why  a particular phenomenon occurs — and it is testable because it generates expectations about what we should observe in different situations. If the hypothesis is accurate, then we’d expect that, for example, sugar processed to a powder should dissolve more quickly than granular sugar. Students could examine rates of dissolution of many different substances in powdered, granular, and pellet form to further test the idea. The statement “Table salt will dissolve in water more quickly than rock salt” is not a hypothesis, but an expectation generated by a hypothesis. Textbooks and science labs can lead to confusions about the difference between a hypothesis and an expectation regarding the outcome of a scientific test. To learn more about scientific hypotheses, visit  Science at multiple levels  in our section on how science works.

In everyday language, the word  theory  is often used to mean a hunch with little evidential support. Scientific theories, on the other hand, are broad explanations for a wide range of phenomena. They are concise (i.e., generally don’t have a long list of exceptions and special rules), coherent, systematic, and can be used to make predictions about many different sorts of situations. A theory is most  acceptable  to the scientific community when it is strongly supported by many different lines of evidence — but even theories may be modified or overturned if warranted by new evidence and perspectives. To learn more about scientific theories, visit  Science at multiple levels  in our section on how science works.

Falsifiable

The word  falsifiable  isn’t used much in everyday language, but when it is, it is often applied to ideas that have been shown to be untrue. When that’s the case — when an idea has been shown to be false — a scientist would say that it has been falsified. A falsifi able  idea, on the other hand, is one for which there is a conceivable  test  that might produce evidence proving the idea false. Scientists and others influenced by the ideas of the philosopher Karl Popper sometimes assert that only falsifiable ideas are scientific. However, we now recognize that science cannot once-and-for-all prove any idea to be false (or true for that matter). Furthermore, it’s clear that evidence can play a role in supporting particular ideas over others — not just in ruling some ideas out, as implied by the falsifiability criterion. When a scientist says  falsifiable , he or she probably actually means something like  testable , the term we use in this website to avoid confusion. A testable idea is one about which we could gather evidence to help determine whether or not the idea is accurate.

Uncertainty

In everyday language,  uncertainty  suggests the state of being unsure of something. Scientists, however, usually use the word when referring to measurements. The uncertainty of a measurement (not to be confused with the inherent provisionality of all scientific ideas!) is the range of values within which the true value is likely to fall. In science, uncertainty is not a bad thing; it’s simply a fact of life. Every measurement has some uncertainty. If you measure the length of a pen with a standard ruler, you won’t be able to tell whether its length is 5.880 inches, 5.875 inches, or 5.870 inches. A ruler with more precision will help narrow that range, but cannot eliminate uncertainty entirely. For more on a related idea, see our discussion of  error  below.

In everyday language, an error is simply a mistake, but in science, error has a precise statistical meaning. An error is the difference between a measurement and the true value, often resulting from taking a  sample . For example, imagine that you want to know if corn plants produce more massive ears when grown with a new fertilizer, and so you weigh ears of corn from those plants. You take the mass of your sample of 50 ears of corn and calculate an average. That average is a good estimate of what you are really interested in: the average mass of  all  ears of corn that could be grown with this fertilizer. Your estimate is not a mistake — but it does have an error (in the statistical sense of the word) since your estimate is not the true value. Sampling error of the sort described above is inherent whenever a smaller sample is taken to represent a larger entity. Another sort of error results from systematic biases in measurement (e.g., if your scale were calibrated improperly, all of your measurements would be off). Systematic error biases measurements in a particular direction and can be more difficult to quantify than sampling error.

In everyday language,  prediction  generally refers to something that a fortune teller makes about the future. In science, the term  prediction  generally means “what we would expect to happen or what we would expect to observe if this idea were accurate.” Sometimes, these scientific predictions have nothing at all to do with the future. For example, scientists have hypothesized that a huge asteroid struck the Earth 4.5 billion years ago, flinging off debris that formed the moon. If this idea were true, we would  predict  that the moon today would have a similar composition to that of the Earth’s crust 4.5 billion years ago — a prediction which does seem to be accurate. This hypothesis deals with the deep history of our solar system and yet it involves predictions — in the scientific sense of the word. Ironically, scientific predictions often have to do with past events. In this website, we’ve tried to reduce confusion by using the words  expect and  expectation  instead of  predict  and  prediction . To learn more, visit  Predicting the past  in our section on the core of science.

Belief/believe

When we, in everyday language, say that we believe in something, we may mean many things — that we support a cause, that we have faith in an idea, or that we think something is accurate. The word  belief  is often associated with ideas about which we have strong convictions, regardless of the evidence for or against them. This can generate confusion when a scientist claims to “believe in” a scientific hypothesis or theory. In fact, the scientist probably means that he or she “ accepts ” the idea — in other words, that he or she thinks the scientific idea is the most accurate available based on a critical evaluation of the evidence. Scientific ideas should always be accepted or rejected based on the evidence for or against them — not based on faith, dogma, or personal conviction.

Roadblocks to learning science

In school, many students get the wrong impression of science. While not technically misconceptions, these overgeneralizations are almost always inaccurate — and can make it more difficult for the students who hold them to learn science.

MISCONCEPTION: Science is boring.

  Memorizing facts from a textbook can be boring — but science is much more than the knowledge that makes its way into school books. Science is an ongoing and unfinished process of discovery. Some scientists travel all over the world for their research. Others set up experiments that no one has ever tried before. And all scientists are engaged in a thrilling quest — to learn something brand new about the natural world. Some parts of scientific training or investigations may be tedious, but science itself is exciting! To see how a scientific perspective can make the world a more exciting and intriguing place, visit our side trip  Think science .

MISCONCEPTION: Science isn't important in my life.

It’s easy to think that what scientists do in far-off laboratories and field stations has little relevance to your everyday life — after all, not many of us deal with super colliders or arctic plankton on a regular basis — but take another look around you. All the technologies, medical advances, and knowledge that improve our lives everyday are partly the result of scientific research. Furthermore, the choices you make when you vote in elections and support particular causes can influence the course of science. Science is deeply interwoven with our everyday lives. To see how society influences science, visit  Science and society . To learn more about how scientific advances affect your life, visit  What has science done for you lately?

MISCONCEPTION: I am not good at science.

Some students find science class difficult — but this doesn’t translate to not being good at science. First of all, school science can be very different from real science. The background knowledge that one learns in school is important for practicing scientists, but it is only part of the picture. Scientific research also involves creative problem-solving, communicating with others, logical reasoning, and many other skills that might or might not be a part of every science class. Second, science encompasses a remarkably broad set of activities. So maybe you don’t care much for the periodic table — but that doesn’t mean that you wouldn’t be great at observing wild chimpanzee behavior, building computer models of tectonic plate movement, or giving talks about psychology experiments at scientific meetings. Often when a student claims to “not be good at science,” it really just means that he or she hasn’t yet found a part of science that clicks with his or her interests and talents.

1 Ecklund, E.H., and C.P. Scheitle. 2007. Religion among academic scientists: Distinctions, disciplines, and demographics.  Social Problems  54(2):289-307.

• Teaching resources
• Unfortunately, many textbooks promulgate misconceptions about the nature and process of science. Use this list to review your textbook, and then discuss any misrepresentations with students.
• You can highlight misconceptions about science that are promulgated in the media by starting a bulletin board that highlights examples of misconceptions found in the popular press — for example, misuses of the word theory, implications that scientists always use “the scientific method,” or that experimental science is more rigorous than non-experimental science.
• Use word lists to combat misconceptions about science that stem from vocabulary mix-ups. Find out how in this article distributed with permission from Science Scope.

Alignment with science standards

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