control setup vs experimental setup

The Difference Between Control Group and Experimental Group

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In an experiment , data from an experimental group is compared with data from a control group. These two groups should be identical in every respect except one: the difference between a control group and an experimental group is that the independent variable is changed for the experimental group, but is held constant in the control group.

Key Takeaways: Control vs. Experimental Group

• The control group and experimental group are compared against each other in an experiment. The only difference between the two groups is that the independent variable is changed in the experimental group. The independent variable is "controlled", or held constant, in the control group.
• A single experiment may include multiple experimental groups, which may all be compared against the control group.
• The purpose of having a control is to rule out other factors which may influence the results of an experiment. Not all experiments include a control group, but those that do are called "controlled experiments."
• A placebo may also be used in an experiment. A placebo isn't a substitute for a control group because subjects exposed to a placebo may experience effects from the belief they are being tested; this itself is known as the placebo effect.

What Are Is an Experimental Group in Experiment Design?

An experimental group is a test sample or the group that receives an experimental procedure. This group is exposed to changes in the independent variable being tested. The values of the independent variable and the impact on the dependent variable are recorded. An experiment may include multiple experimental groups at one time.

A control group is a group separated from the rest of the experiment such that the independent variable being tested cannot influence the results. This isolates the independent variable's effects on the experiment and can help rule out alternative explanations of the experimental results.

While all experiments have an experimental group, not all experiments require a control group. Controls are extremely useful where the experimental conditions are complex and difficult to isolate. Experiments that use control groups are called controlled experiments .

A Simple Example of a Controlled Experiment

A simple example of a controlled experiment may be used to determine whether or not plants need to be watered to live. The control group would be plants that are not watered. The experimental group would consist of plants that receive water. A clever scientist would wonder whether too much watering might kill the plants and would set up several experimental groups, each receiving a different amount of water.

Sometimes setting up a controlled experiment can be confusing. For example, a scientist may wonder whether or not a species of bacteria needs oxygen in order to live. To test this, cultures of bacteria may be left in the air, while other cultures are placed in a sealed container of nitrogen (the most common component of air) or deoxygenated air (which likely contained extra carbon dioxide). Which container is the control? Which is the experimental group?

Control Groups and Placebos

The most common type of control group is one held at ordinary conditions so it doesn't experience a changing variable. For example, If you want to explore the effect of salt on plant growth, the control group would be a set of plants not exposed to salt, while the experimental group would receive the salt treatment. If you want to test whether the duration of light exposure affects fish reproduction, the control group would be exposed to a "normal" number of hours of light, while the duration would change for the experimental group.

Experiments involving human subjects can be much more complex. If you're testing whether a drug is effective or not, for example, members of a control group may expect they will not be unaffected. To prevent skewing the results, a placebo may be used. A placebo is a substance that doesn't contain an active therapeutic agent. If a control group takes a placebo, participants don't know whether they are being treated or not, so they have the same expectations as members of the experimental group.

However, there is also the placebo effect to consider. Here, the recipient of the placebo experiences an effect or improvement because she believes there should be an effect. Another concern with a placebo is that it's not always easy to formulate one that truly free of active ingredients. For example, if a sugar pill is given as a placebo, there's a chance the sugar will affect the outcome of the experiment.

Positive and Negative Controls

Positive and negative controls are two other types of control groups:

• Positive control groups are control groups in which the conditions guarantee a positive result. Positive control groups are effective to show the experiment is functioning as planned.
• Negative control groups are control groups in which conditions produce a negative outcome. Negative control groups help identify outside influences which may be present that were not unaccounted for, such as contaminants.
• Bailey, R. A. (2008). Design of Comparative Experiments . Cambridge University Press. ISBN 978-0-521-68357-9.
• Chaplin, S. (2006). "The placebo response: an important part of treatment". Prescriber : 16–22. doi: 10.1002/psb.344
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
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Tackle Control Set-up Questions Like A Pro

Posted by Lim Zi Ai | Jul 14, 2016 | Experimental Techniques , Primary 5 Science , Primary 6 Science , Primary School Science Techniques | 0 |

Experiment-centric questions are increasingly common in primary school examination papers today.

There are typically six types of experiment-centric questions that can be tested:

• Relationship – What is the relationship between X and Y?
• Fair Test – How do we ensure a fair test?
• Reliability – How can the experiment be more reliable?
• Aim – What is the aim of the experiment?
• Conclusion – What can you conclude from the experiment?
• Control Set-up – What is the purpose of the control set-up?

I’m sure you’ve probably seen a variation of one of the above questions in your child’s examination paper.

Read Also Tackling Conclusion Type Questions FAQ: The Pique Lab – Experimental Techniques Masterclass The CUE Method To Tackle Data-Based Questions

Many students often struggle to structure their answers in a coherent & scientific manner, causing them to lose marks unnecessarily.

The good news is that we know what are the possible experiment-centric questions that can be tested!

We’re able to help your child prepare these answers ahead of their examinations & execute them when they see something similar. 🙂

Isn’t that amazing?

In our previous article, we discussed tackling conclusion-type questions , arguably one of the more challenging experiment-centric questions.

Today, we’ll be looking at how to tackle control set-up questions . It is often expressed in the following format:

What is the purpose of the control set-up?

For this particular question, students are often able to identify the changed variable and the measured variable in the question. The challenge lies in using the correctly identified variables to structure their answers properly.

As such, I would like to introduce a template answer to help your child with control set-up questions.

Thought Process

A control set-up is often needed to ensure that the experiment is valid & accurate. It serves as a baseline for the comparison of the results of the main experiment.

The control set-up will also rule out other environmental variables from affecting the results and eventually help to establish the conclusion of the experiment.

Ultimately, the control set-up is in place to ensure that the measured variable (dependent variable)  is affected only by the changed variable (independent variable)  and not any other variable in the experiment.

Template Answer

The purpose of preparing Set-up __ is to act as a control set-up to ensure that the _____________ (measured variable) is only caused by the ___________ (changed variable) and not any other variables in the experiment.

Final Answer

With reference to part (b) of the above question…

The purpose of preparing Set-up B is to act as a control set-up to ensure that the change observed in the limewater (if any) is only caused by the gas produced during decomposition and not any other variables in the experiment.

I hope that this article has shown you how to apply to correct template answer to easily tackle experiment-centric questions on control set-ups!

Over the past 13 years, Ms. Zi Ai has worked with primary and secondary students from a wide spectrum of backgrounds. She is highly proficient in helping her students navigate the thought processes and answering techniques required to excel in PSLE Science examination. As a Psychology graduate from the National University of Singapore, she actively seeks to use her knowledge to get her students to be intrinsically motivated to learn Science. Her secret lies in helping the child rediscover their interest for learning through her wide arsenal of humorous and inspiring teaching methods.

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What Is a Control Setup in Science?

A control setup in science uses the same conditions and the same equipment as the experimental setup; however, there are no variables tested in the control setup, as there are in the experimental setup. A control setup can include the use of a control group, which takes place when the experiment includes people.

The people in the control group act as a control set-up. They do not receive the factor or active medication that the people do in the experimental group, which acts as the experimental setup.

A controlled experiment can use a control group or a controlled setup, but is designed so that only one variable is manipulated at a time. This is necessary for the experiment to produce accurate results because if there are multiple variables then the scientists cannot know which variable produced which result.

The scientific method is used in the experimental process and in a controlled setup. The scientific method has several steps, which are: ask a question, do background research, construct a hypothesis, test the hypothesis by doing an experiment, analyze the data and draw a conclusion and communicate the results. The scientific method is the method by which all experiments are conducted and allows scientists to ask and answer scientific questions through observations and experiments.

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HOW TO TACKLE CONTROL SET-UP QUESTIONS

August 19, 2019 • Control Set-up • PSLE Science Answering Techniques

Control Set-up   :  Experimental-based Questions

Experimental-based questions are regularly tested in Primary School Science examinations.  In this article I will share with you three question samples on how to tackle questions involving control set-ups by using " 3C " method ( C ontrol -C ompare -C onfirm ) .

(i)   What is a Control Set-up? 

• An experimental set-up which is used for   comparison   in order to   confirm  the conclusion   of an experiment.
• An experimental set-up to show that the results obtained and observations made are only due to material tested and not other external factors. 

(ii)   Control Set-up Question is often expressed in the following format:

• Variant 1: Why is there a need for set-up B?
• Variant 2: Why is there a need for a control set-up?
• Variant 3: Draw and label a control set-up for the experiment.

(iii)   How to answer Variant 1, 2 and 3 Questions?

• Variant 1 : It acts as a control set-up to compare and confirm that the (Measured variable / Dependent variable) is only due to the (Changed variable / Independent variable) and not due to other variables in the experiment. 
• Variant 2   :  It is used t o   compare   and   confirm   that the   (Measured variable / Dependent variable)   is only due to the   (Changed variable / Independent variable)   and not due to other variables in the experiment. 
• Variant 3   :  To draw the control set-up is to  change/remove  the  (Changed variable / Independent variable) in the experimental set-up so as to prove that any change in result is only due to the (Changed variable / independent variable) and not because of other variables in the experiment. 

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What is the difference between the Method and Experimental Setup section

I am writing a Computer Science paper, however my supervisor wants me to describe the methodology in a more general form in the Method section. In the Experimental Setup section I dive into the details. My question is, what is general ?

I always assumed that the Method and Experimental Setup were one section were you describe your setup/method in detail.

• computer-science

• Quite obviously, the Method section is supposed to describe approaches / methods / techniques without implementation details . On the other hand, the Experimental Setup section is the place where those implementation details belong. –  Aleksandr Blekh Commented May 2, 2016 at 4:38

The answer to this question depends a little on the field of application.

In fields like computational sciences, this is the section where you describe a set of algorithms to be implemented. In fields like material engineering and life sciences, you describe the general procedure to be followed to solve the problem defined in the problem statement. " General " here refers to more of an overview of your implementation rather than its deeper aspects.

Experimental Setup

This is where you explain the implementation aspects in detail. You describe where and how the algorithms are applied in computation. You depict the use of instruments, apparatus, and other tangible items in material engineering and sciences.

In short, I presume your supervisor wants you to give a brief overview of your implementation in the Method section and would like you to explain it in detail in the Experimental Setup section. However, the level of detail can vary widely among the above sections.

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Control Set-up: Acing Experiment-Based Questions in PSLE Science

This is the last of 5 articles on experiment-based questions in PSLE Science . Experimental-based questions are regularly tested in Science exam papers and it is important that students have mastery over the concepts tested.

The focus for today’s article is on control set-ups, another question type dreaded by students. They either do not understand the purpose of a control set-up or do not know how to draw a control set-up. Here, I will give you two specific examples on how to tackle questions involving control set-ups.

Purpose of a Control Set-up

• It is used for comparison in order to verify the conclusion of an experiment.
• To ensure that the measured variable (dependent variable) is affected only by the changed variable (independent variable) and not any other (control) variables in the experiment.

Scientist Strange carried out an experiment as shown below. He left both set-ups in a warm and dark cupboard for two days. He observed that the seeds in Set-up X germinated and the limewater turned cloudy while the limewater in Set-up Y remained clear.

What is the aim of the experiment and purpose of having Set-up Y?

• The only changed variable (independent variable) → presence of seeds
• Measured variable (dependent variable) → if carbon dioxide was given out by plant
• Control variable → all other variables in the experiment like size of beakers, amount of limewater, presence of rubber stoppers in both beakers, same location where experiment was carried out, etc.
• Since the aim of an experiment is related to the independent and dependent variable, the aim of the experiment is to find out if germinating seeds give out carbon dioxide .
• Purpose of Set-up Y → A control set-up to confirm that carbon dioxide was given out by the germinating seeds .

How to Draw the Control Set-up for an Experiment?

A good way to know how to draw the control set-up is to change the independent variable in the control set-up so as to prove that any change in result is only due to the independent variable and not because of other control variables .

This concludes the last of 5 articles on Experiment-Based Questions that are tested in school examinations and PSLE Science paper. With a subscription to OwlSmart , students get access over 200 experiment-based questions for PSLE Science with concise explanations. Students who practised more on these questions have shown to have a higher level of confidence in tackling them in the PSLE.

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Control Group vs Experimental Group

Julia Simkus

Editor at Simply Psychology

BA (Hons) Psychology, Princeton University

Julia Simkus is a graduate of Princeton University with a Bachelor of Arts in Psychology. She is currently studying for a Master's Degree in Counseling for Mental Health and Wellness in September 2023. Julia's research has been published in peer reviewed journals.

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Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

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

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

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

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In a controlled experiment , scientists compare a control group, and an experimental group is identical in all respects except for one difference – experimental manipulation.

Differences

Unlike the experimental group, the control group is not exposed to the independent variable under investigation. So, it provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Almost all experimental studies are designed to include a control group and one or more experimental groups. In most cases, participants are randomly assigned to either a control or experimental group.

Because participants are randomly assigned to either group, we can assume that the groups are identical except for manipulating the independent variable in the experimental group.

It is important that every aspect of the experimental environment is the same and that the experimenters carry out the exact same procedures with both groups so researchers can confidently conclude that any differences between groups are actually due to the difference in treatments.

Control Group

A control group consists of participants who do not receive any experimental treatment. The control participants serve as a comparison group.

The control group is matched as closely as possible to the experimental group, including age, gender, social class, ethnicity, etc.

The difference between the control and experimental groups is that the control group is not exposed to the independent variable , which is thought to be the cause of the behavior being investigated.

Researchers will compare the individuals in the control group to those in the experimental group to isolate the independent variable and examine its impact.

The control group is important because it serves as a baseline, enabling researchers to see what impact changes to the independent variable produce and strengthening researchers’ ability to draw conclusions from a study.

Without the presence of a control group, a researcher cannot determine whether a particular treatment truly has an effect on an experimental group.

Control groups are critical to the scientific method as they help ensure the internal validity of a study.

Assume you want to test a new medication for ADHD . One group would receive the new medication, and the other group would receive a pill that looked exactly the same as the one that the others received, but it would be a placebo. The group that takes the placebo would be the control group.

Types of Control Groups

Positive control group.

• A positive control group is an experimental control that will produce a known response or the desired effect.
• A positive control is used to ensure a test’s success and confirm an experiment’s validity.
• For example, when testing for a new medication, an already commercially available medication could serve as the positive control.

Negative Control Group

• A negative control group is an experimental control that does not result in the desired outcome of the experiment.
• A negative control is used to ensure that there is no response to the treatment and help identify the influence of external factors on the test.
• An example of a negative control would be using a placebo when testing for a new medication.

Experimental Group

An experimental group consists of participants exposed to a particular manipulation of the independent variable. These are the participants who receive the treatment of interest.

Researchers will compare the responses of the experimental group to those of a control group to see if the independent variable impacted the participants.

An experiment must have at least one control group and one experimental group; however, a single experiment can include multiple experimental groups, which are all compared against the control group.

Having multiple experimental groups enables researchers to vary different levels of an experimental variable and compare the effects of these changes to the control group and among each other.

Assume you want to study to determine if listening to different types of music can help with focus while studying.

You randomly assign participants to one of three groups: one group that listens to music with lyrics, one group that listens to music without lyrics, and another group that listens to no music.

The group of participants listening to no music while studying is the control group, and the groups listening to music, whether with or without lyrics, are the two experimental groups.

Frequently Asked Questions

1. what is the difference between the control group and the experimental group in an experimental study.

Put simply; an experimental group is a group that receives the variable, or treatment, that the researchers are testing, whereas the control group does not. These two groups should be identical in all other aspects.

2. What is the purpose of a control group in an experiment

A control group is essential in experimental research because it:

Provides a baseline against which the effects of the manipulated variable (the independent variable) can be measured.

Helps to ensure that any changes observed in the experimental group are indeed due to the manipulation of the independent variable and not due to other extraneous or confounding factors.

Helps to account for the placebo effect, where participants’ beliefs about the treatment can influence their behavior or responses.

In essence, it increases the internal validity of the results and the confidence we can have in the conclusions.

3. Do experimental studies always need a control group?

Not all experiments require a control group, but a true “controlled experiment” does require at least one control group. For example, experiments that use a within-subjects design do not have a control group.

In  within-subjects designs , all participants experience every condition and are tested before and after being exposed to treatment.

These experimental designs tend to have weaker internal validity as it is more difficult for a researcher to be confident that the outcome was caused by the experimental treatment and not by a confounding variable.

4. Can a study include more than one control group?

Yes, studies can include multiple control groups. For example, if several distinct groups of subjects do not receive the treatment, these would be the control groups.

5. How is the control group treated differently from the experimental groups?

The control group and the experimental group(s) are treated identically except for one key difference: exposure to the independent variable, which is the factor being tested. The experimental group is subjected to the independent variable, whereas the control group is not.

This distinction allows researchers to measure the effect of the independent variable on the experimental group by comparing it to the control group, which serves as a baseline or standard.

Bailey, R. A. (2008). Design of Comparative Experiments. Cambridge University Press. ISBN 978-0-521-68357-9.

Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.

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Understanding Experimental Controls

• Experimentation

Much of the training that scientists receive in graduate school is experiential, you learn how to do an experiment by working in a laboratory and performing experiments. In my opinion, not enough time and effort is devoted to understanding the philosophy and methods of experimental design.

An experiment without the proper controls is meaningless. Controls allow the experimenter to minimize the effects of factors other than the one being tested. It’s how we know an experiment is testing the thing it claims to be testing.

This goes beyond science — controls are necessary for any sort of experimental testing, no matter the subject area. This is often why so many bibliometric studies of the research literature are so problematic. Inadequate controls are often performed which fail to eliminate the effects of confounding factors, leaving the causality of any effect seen to be undetermined.

Novartis’ David Glass has put together the videos below, showing some of the basics of experimental validation and controls (Full disclosure: I was an editor on the first edition of David’s book on experimental design). These short videos offer quick lessons in positive and negative controls, as well as how to validate your experimental system.

These are great starting points, and I highly recommend Glass’ book, now in its second edition , if you want to dig deeper and understand the nuances of the different types of negative and positive controls, not to mention method and reagent controls, subject controls, assumption controls and experimentalist controls.

David Crotty

David Crotty is a Senior Consultant at Clarke & Esposito, a boutique management consulting firm focused on strategic issues related to professional and academic publishing and information services. Previously, David was the Editorial Director, Journals Policy for Oxford University Press. He oversaw journal policy across OUP’s journals program, drove technological innovation, and served as an information officer. David acquired and managed a suite of research society-owned journals with OUP, and before that was the Executive Editor for Cold Spring Harbor Laboratory Press, where he created and edited new science books and journals, along with serving as a journal Editor-in-Chief. He has served on the Board of Directors for the STM Association, the Society for Scholarly Publishing and CHOR, Inc., as well as The AAP-PSP Executive Council. David received his PhD in Genetics from Columbia University and did developmental neuroscience research at Caltech before moving from the bench to publishing.

7 Thoughts on "Understanding Experimental Controls"

We could add one more necessary control in this experiment–controlling for variability in individual response.

In the three videos, the experimenter may only detect differences between groups (or average differences). He is unable to detect changes in individuals. Some participants may be more sensitive to caffeine than others, some may show negative changes, and some may show no changes at all. If we take the blood pressure of participants before they drink coffee, we have a baseline measurement for all individuals. We also have a check on whether the experimenter was able to randomly assign participants to each treatment group.

In effect, each individual is their own control, with a before and after measurement. The experimenter is looking at the change in response of the individual rather than the average effect of the group. It is a much more sensitive way to structure and analyze experiments like this.

• By Phil Davis
• Nov 2, 2018, 8:57 AM

Agreed, these videos only skim the surface (his book goes into much greater detail about a much wider range of controls).

• By David Crotty
• Nov 2, 2018, 9:05 AM

Most experimenters who use random assignment to control and treatment groups have found that post-test only design works as well as pre-/post-test design.

• Nov 2, 2018, 10:01 AM

I don’t see how. By controlling for a potentially large source of variability—the individual participant—statistical tests become much more sensitive to changes than averaging all of that variability by group in a simple post-test design. Second, it is a check to see whether the randomization of participants into groups was successful. In many RTCs in the clinical sciences, there is recruitment bias, allowing for the sicker patients to be placed in the treatment group, for example.

• Nov 2, 2018, 12:55 PM

No mention of Institutional Review Board?! The IRB will raise Dr. Johnson’s own blood pressure.

And then there’s the issue of Dr. Johnson’s White Coat — that might trigger considerable individual variation. (My own blood pressure readings change markedly in the course of a visit to the doctor. )

• Nov 2, 2018, 4:59 PM

I believe that IRB approval is discussed in the video on system validation.

• Nov 2, 2018, 5:02 PM

Late to the debate, but I think those are wonderful. Maybe next Control Kitty will ask just how he assembled all those volunteers for his test to be representative and blinding to minimize bias. Were they self-selected? A bunch of caffeine habituated javaheads who responded to an ad in the coffee shop? I could see another video on randomization and sampling frames. I’m sure David Glass’s book goes into all that, but well, I have a shelf full of related books and I’m unlikely to benefit from and want to buy another. Unless maybe he hooks with another clever video or two. Go Kitty! Except, ~900 views! That’s sad. I might have sneak in citations to them. (I tend to get chastised by reviewers/editors for citing non-scholarly sources.) Something like this might slip under the editor’s radar: Glass, D. 2018. Experimental Design for Biologists: 1. System Validation. Video (4:06 minutes). YouTube. https://www.youtube.com/watch?v=qK9fXYDs–8 [Accessed November 11, 2018].

• By Chris Mebane
• Nov 12, 2018, 12:17 AM

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• Control Groups and Treatment Groups | Uses & Examples

Control Groups and Treatment Groups | Uses & Examples

Published on July 3, 2020 by Lauren Thomas . Revised on June 22, 2023.

In a scientific study, a control group is used to establish causality by isolating the effect of an independent variable .

Here, researchers change the independent variable in the treatment group and keep it constant in the control group. Then they compare the results of these groups.

Using a control group means that any change in the dependent variable can be attributed to the independent variable. This helps avoid extraneous variables or confounding variables from impacting your work, as well as a few types of research bias , like omitted variable bias .

Table of contents

Control groups in experiments, control groups in non-experimental research, importance of control groups, other interesting articles, frequently asked questions about control groups.

Control groups are essential to experimental design . When researchers are interested in the impact of a new treatment, they randomly divide their study participants into at least two groups:

• The treatment group (also called the experimental group ) receives the treatment whose effect the researcher is interested in.
• The control group receives either no treatment, a standard treatment whose effect is already known, or a placebo (a fake treatment to control for placebo effect ).

The treatment is any independent variable manipulated by the experimenters, and its exact form depends on the type of research being performed. In a medical trial, it might be a new drug or therapy. In public policy studies, it could be a new social policy that some receive and not others.

In a well-designed experiment, all variables apart from the treatment should be kept constant between the two groups. This means researchers can correctly measure the entire effect of the treatment without interference from confounding variables .

• You pay the students in the treatment group for achieving high grades.
• Students in the control group do not receive any money.

Studies can also include more than one treatment or control group. Researchers might want to examine the impact of multiple treatments at once, or compare a new treatment to several alternatives currently available.

• The treatment group gets the new pill.
• Control group 1 gets an identical-looking sugar pill (a placebo)
• Control group 2 gets a pill already approved to treat high blood pressure

Since the only variable that differs between the three groups is the type of pill, any differences in average blood pressure between the three groups can be credited to the type of pill they received.

• The difference between the treatment group and control group 1 demonstrates the effectiveness of the pill as compared to no treatment.
• The difference between the treatment group and control group 2 shows whether the new pill improves on treatments already available on the market.

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Although control groups are more common in experimental research, they can be used in other types of research too. Researchers generally rely on non-experimental control groups in two cases: quasi-experimental or matching design.

Control groups in quasi-experimental design

While true experiments rely on random assignment to the treatment or control groups, quasi-experimental design uses some criterion other than randomization to assign people.

Often, these assignments are not controlled by researchers, but are pre-existing groups that have received different treatments. For example, researchers could study the effects of a new teaching method that was applied in some classes in a school but not others, or study the impact of a new policy that is implemented in one state but not in the neighboring state.

In these cases, the classes that did not use the new teaching method, or the state that did not implement the new policy, is the control group.

Control groups in matching design

In correlational research , matching represents a potential alternate option when you cannot use either true or quasi-experimental designs.

In matching designs, the researcher matches individuals who received the “treatment”, or independent variable under study, to others who did not–the control group.

Each member of the treatment group thus has a counterpart in the control group identical in every way possible outside of the treatment. This ensures that the treatment is the only source of potential differences in outcomes between the two groups.

Control groups help ensure the internal validity of your research. You might see a difference over time in your dependent variable in your treatment group. However, without a control group, it is difficult to know whether the change has arisen from the treatment. It is possible that the change is due to some other variables.

If you use a control group that is identical in every other way to the treatment group, you know that the treatment–the only difference between the two groups–must be what has caused the change.

For example, people often recover from illnesses or injuries over time regardless of whether they’ve received effective treatment or not. Thus, without a control group, it’s difficult to determine whether improvements in medical conditions come from a treatment or just the natural progression of time.

Risks from invalid control groups

If your control group differs from the treatment group in ways that you haven’t accounted for, your results may reflect the interference of confounding variables instead of your independent variable.

Minimizing this risk

A few methods can aid you in minimizing the risk from invalid control groups.

• Ensure that all potential confounding variables are accounted for , preferably through an experimental design if possible, since it is difficult to control for all the possible confounders outside of an experimental environment.
• Use double-blinding . This will prevent the members of each group from modifying their behavior based on whether they were placed in the treatment or control group, which could then lead to biased outcomes.
• Randomly assign your subjects into control and treatment groups. This method will allow you to not only minimize the differences between the two groups on confounding variables that you can directly observe, but also those you cannot.

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

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Creating Experimental Setups

• First Online: 12 April 2023

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• Raban Iten 2  

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Creating experimental setups is a fundamental step in a physicist’s discovery process. This task is particularly challenging for quantum systems, since the behavior of such systems is often unintuitive. In this chapter, we discuss how a special kind of reinforcement learning, called projective simulation, can help to automate the creation of experimental setups.

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A Hilbert space is a real or complex inner product space that is a complete metric space with respect to the distance function induced by the inner product. The distance function, induced by an inner product \(\left\langle \cdot |\cdot \right\rangle \) , between two vectors x and y is defined by \(\left\langle x-y|x-y\right\rangle \) .

The notation \(\left\langle \psi _{AB}|\psi _{AB}\right\rangle \) abbreviates the expression \(\left\langle | \psi _{AB} \rangle || \psi _{AB} \rangle \right\rangle \) and is actually one of the underlying reasons why it is common to bracket a quantum state by \(| \cdot \rangle \) , which is called the “ket”-notation. Together with the “bra”-notation \(\langle \psi _{AB} |\) , denoting the complex conjugate row vector of the column vector \(\psi _{AB}\) , the “braket”-notation \(\left\langle \psi _{AB}|\psi _{AB}\right\rangle \) can be read as the matrix multiplication of \(\langle \psi _{AB} |\) with \(| \psi _{AB} \rangle \) .

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Iten, R. (2023). Creating Experimental Setups. In: Artificial Intelligence for Scientific Discoveries. Springer, Cham. https://doi.org/10.1007/978-3-031-27019-2_5

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What is a control setup ?

A control setup in science uses the same conditions and the same equipment as the experimental setup; however, there are no variables tested in the control setup, as there are in the experimental setup. a control setup can include the use of a control group, which takes place when the experiment includes people. the people in the control group act as a control set-up. they do not receive the factor or active medication that the people do in the experimental group, which acts as the experimental setup. a controlled experiment can use a control group or a controlled setup, but is designed so that only one variable is manipulated at a time. this is necessary for the experiment to produce accurate results because if there are multiple variables then the scientists cannot know which variable produced which result. the scientific method is used in the experimental process and in a controlled setup. the scientific method has several steps, which are: ask a question, do background research, construct a hypothesis, test the hypothesis by doing an experiment, analyze the data and draw a conclusion and communicate the results. the scientific method is the method by which all experiments are conducted and allows scientists to ask and answer scientific questions through observations and experiments..

Fluorination of Methane can be controlled in a Laboratory setup - True or False?

In the above setup, what is X?

What is the inference of the experimental setup shown below?

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article heading should be "Experiment setup" or "Experimental setup"?

My advisor insists on using a heading "Experimental Setup" in his science journal articles. I always cringed a little, thinking it should be "Experiment setup" instead. Now I am writing an article and in his edits he wants me to add the -al.

To me, "experimental setup" sounds like the setup itself is experimental, but "experiment setup" sounds more like we set up an experiment. Technically, we set up an experiment, and the setup itself was not the experiment. I suppose the root of my question in this case is, is the word "experiment" supposed to be an adjective or a noun? Hopefully that explanation makes my grievance clear..

English is his 2nd language, and my first, so he won't mind me questioning it.

Does anyone have a definitive answer to that one? Thank in advance! -Curious Grad Student

• compound-adjectives

• 2 I completely agree with you on that. It reads as a setup that you are trying out. –  Avon Commented Jul 10, 2015 at 22:08

3 Answers 3

He is following convention. Try looking at other papers, this is the standard term.

If you say "Experiment Setup" you may feel better but your readers will wonder what you are trying to prove - worse they may think you have made an error.

Maybe, as a compromise, you could say "Setup of the Experiment" (?)

• I agree, this does seem to be the norm. In the long run, I will probably just go with The Boss and do it his way. Thank you! –  GradStudent Commented Jul 10, 2015 at 23:14
• It is sometimes the case that almost everybody gets it wrong. Especially when many follow like sheep and do not question. This applies to life as well as to language. –  Brian Hitchcock Commented Jul 11, 2015 at 9:35

Here's chapter subheading C from the book Quantum Mechanics by K. T. Hecht:

C   Complementary Experimental Setup

The Ngram Viewer sides with your advisor, finding the usage with -al over fifty times as popular as the usage without.

I understand your unease. It's the same one I get when I hear the words "oversight committee." Are they overseeing something or overlooking it?

• I've never seen the Ngram viewer before. What a cool tool! –  GradStudent Commented Jul 10, 2015 at 23:18

Is there a reason why 'methodology' is not a suitable alternative? That's what I would go with in this situation to avoid confusion.

Also, just a thought, are you absolutely sure that the setup itself is not experimental? Typically primary research papers will cite previously published literature that outlines the methods that were used in the research or otherwise state that the methods were developed by the authors. Often there will be a citation in addition to some specified modifications to that protocol that the authors employed in their research. Either way, if it hasn't yet been used by other researchers to reproduce data then I would say it's fair to refer to novel setups as "experimental" experiment setups.

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