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What Is a Controlled Experiment? | Definitions & Examples

What Is a Controlled Experiment? | Definitions & Examples

Published on April 19, 2021 by Pritha Bhandari . Revised on June 22, 2023.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

holding variables at a constant or restricted level (e.g., keeping room temperature fixed).
measuring variables to statistically control for them in your analyses.
balancing variables across your experiment through randomization (e.g., using a random order of tasks).

Why does control matter in experiments, methods of control, problems with controlled experiments, other interesting articles, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables. Strong validity also helps you avoid research biases , particularly ones related to issues with generalizability (like sampling bias and selection bias .)

Your independent variable is the color used in advertising.
Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

Design and description of the meal,
Study environment (e.g., temperature or lighting),
Participant’s frequency of buying fast food,
Participant’s familiarity with the specific fast food brand,
Participant’s socioeconomic status.

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You can control some variables by standardizing your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., ad color) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with color blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment (e.g., a placebo to control for a placebo effect ), and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

To test the effect of colors in advertising, each participant is placed in one of two groups:

A control group that’s presented with red advertisements for a fast food meal.
An experimental group that’s presented with green advertisements for the same fast food meal.

Random assignment

To avoid systematic differences and selection bias between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a “true experiment”—it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers—or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs and is critical for avoiding several types of research bias .

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses , leading to observer bias . In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses. These are called demand characteristics . If participants behave a particular way due to awareness of being observed (called a Hawthorne effect ), your results could be invalidated.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

You use an online survey form to present the advertisements to participants, and you leave the room while each participant completes the survey on the computer so that you can’t tell which condition each participant was in.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity —the extent to which your results can be generalized to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritize control or generalizability in your experiment.

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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In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

A control group that receives a standard treatment, a fake treatment, or no treatment.
Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

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.

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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Understanding Simple vs Controlled Experiments

What Is a Simple Experiment? Controlled Experiment?

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An experiment is a scientific procedure used to test a hypothesis , answer a question, or prove a fact. Two common types of experiments are simple experiments and controlled experiments. Then, there are simple controlled experiments and more complex controlled experiments.

Simple Experiment

Although the phrase "simple experiment" is tossed around to refer to any easy experiment, it's actually a specific type of experiment. Usually, a simple experiment answers a "What would happen if...?" cause-and-effect type of question.

Example: You wonder whether a plant grows better if you mist it with water. You get a sense of how the plant is growing without being misted and then compare this with growth after you start misting it.

Why Conduct a Simple Experiment? Simple experiments usually provide quick answers. They can be used to design more complex experiments, typically requiring fewer resources. Sometimes simple experiments are the only type of experiment available, especially if only one sample exists.

We conduct simple experiments all the time. We ask and answers questions like, "Will this shampoo work better than the one I use?", "Is it okay to use margarine instead of butter in this recipe?", "If I mix these two colors, what will I get?"

Controlled Experiment

Controlled experiments have two groups of subjects. One group is the experimental group and it is exposed to your test. The other group is the control group , which is not exposed to the test. There are several methods of conducting a controlled experiment, but a simple controlled experiment is the most common. The simple controlled experiment has just the two groups: one exposed to the experimental condition and one not-exposed to it.

Example: You want to know whether a plant grows better if you mist it with water. You grow two plants. One you mist with water (your experimental group) and the other you don't mist with water (your control group).

Why Conduct a Controlled Experiment? The controlled experiment is considered a better experiment because it is harder for other factors to influence your results, which could lead you to draw an incorrect conclusion.

Parts of an Experiment

Experiments, no matter how simple or complex, share key factors in common.

Hypothesis A hypothesis is a prediction of what you expect will happen in an experiment. It's easier to analyze your data and draw a conclusion if you phrase the hypothesis as an If-Then or cause and effect statement. For example, a hypothesis might be, "Watering plants with cold coffee will make them grow faster." or "Drinking cola after eating Mentos will cause your stomach to explode." You can test either of these hypotheses and gather conclusive data to support or discard a hypothesis. The null hypothesis or no-difference hypothesis is especially useful because it can be used to disprove a hypothesis. For example, if your hypothesis states, "Watering plants with coffee will not affect plant growth" yet if your plants die, experience stunted growth, or grow better, you can apply statistics to prove your hypothesis incorrect and imply a relationship between the coffee and plant growth does exist.
Experimental Variables Every experiment has variables . The key variables are the independent and dependent variables . The independent variable is the one you control or change to test its effect on the dependent variable. The dependent variable depends on the independent variable. In an experiment to test whether cats prefer one color of cat food over another, you might state the null hypothesis, "Food color does not affect cat food intake." The color of the cat food (e.g., brown, neon pink, blue) would be your independent variable. The amount of cat food eaten would be the dependent variable. Hopefully, you can see how experimental design comes into play. If you offer 10 cats one color of cat food each day and measure how much is eaten by each cat you might get different results than if you put out three bowls of cat food and let the cats choose which bowl to use or you mixed the colors together and looked to see which remained after the meal.
Data The numbers or observations you collect during an experiment are your data. Data are simply facts.
Results Results are your analysis of the data. Any calculations you perform are included in the results section of a lab report.
Conclusion You conclude whether to accept or reject your hypothesis. Usually, this is followed by an explanation of your reasons. Sometimes you may note other outcomes of the experiment, particularly those that warrant further study. For example, if you are testing colors of cat food and you notice the white areas of all the cats in the study turned pink, you might note this and devise a follow-up experiment to determine whether eating the pink cat food affects coat color.
Null Hypothesis Examples
Examples of Independent and Dependent Variables
Difference Between Independent and Dependent Variables
Scientific Method Vocabulary Terms
What Is an Experiment? Definition and Design
The Difference Between Control Group and Experimental Group
What Are the Elements of a Good Hypothesis?
How To Design a Science Fair Experiment
What are Controlled Experiments?
Six Steps of the Scientific Method
Understanding Experimental Groups
What Is a Control Group?
Scientific Variable
What Is a Controlled Experiment?
Null Hypothesis Definition and Examples
What Is the Difference Between a Control Variable and Control Group?

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Controlled Experiment

Reviewed by: BD Editors

Controlled Experiment Definition

A controlled experiment is a scientific test that is directly manipulated by a scientist, in order to test a single variable at a time. The variable being tested is the independent variable , and is adjusted to see the effects on the system being studied. The controlled variables are held constant to minimize or stabilize their effects on the subject. In biology, a controlled experiment often includes restricting the environment of the organism being studied. This is necessary to minimize the random effects of the environment and the many variables that exist in the wild.

In a controlled experiment, the study population is often divided into two groups. One group receives a change in a certain variable, while the other group receives a standard environment and conditions. This group is referred to as the control group , and allows for comparison with the other group, known as the experimental group . Many types of controls exist in various experiments, which are designed to ensure that the experiment worked, and to have a basis for comparison. In science, results are only accepted if it can be shown that they are statistically significant . Statisticians can use the difference between the control group and experimental group and the expected difference to determine if the experiment supports the hypothesis , or if the data was simply created by chance.

Examples of Controlled Experiment

Music preference in dogs.

Do dogs have a taste in music? You might have considered this, and science has too. Believe it or not, researchers have actually tested dog’s reactions to various music genres. To set up a controlled experiment like this, scientists had to consider the many variables that affect each dog during testing. The environment the dog is in when listening to music, the volume of the music, the presence of humans, and even the temperature were all variables that the researches had to consider.

In this case, the genre of the music was the independent variable. In other words, to see if dog’s change their behavior in response to different kinds of music, a controlled experiment had to limit the interaction of the other variables on the dogs. Usually, an experiment like this is carried out in the same location, with the same lighting, furniture, and conditions every time. This ensures that the dogs are not changing their behavior in response to the room. To make sure the dogs don’t react to humans or simply the noise of the music, no one else can be in the room and the music must be played at the same volume for each genre. Scientist will develop protocols for their experiment, which will ensure that many other variables are controlled.

This experiment could also split the dogs into two groups, only testing music on one group. The control group would be used to set a baseline behavior, and see how dogs behaved without music. The other group could then be observed and the differences in the group’s behavior could be analyzed. By rating behaviors on a quantitative scale, statistics can be used to analyze the difference in behavior, and see if it was large enough to be considered significant. This basic experiment was carried out on a large number of dogs, analyzing their behavior with a variety of different music genres. It was found that dogs do show more relaxed and calm behaviors when a specific type of music plays. Come to find out, dogs enjoy reggae the most.

Scurvy in Sailors

In the early 1700s, the world was a rapidly expanding place. Ships were being built and sent all over the world, carrying thousands and thousands of sailors. These sailors were mostly fed the cheapest diets possible, not only because it decreased the costs of goods, but also because fresh food is very hard to keep at sea. Today, we understand that lack of essential vitamins and nutrients can lead to severe deficiencies that manifest as disease. One of these diseases is scurvy.

Scurvy is caused by a simple vitamin C deficiency, but the effects can be brutal. Although early symptoms just include general feeling of weakness, the continued lack of vitamin C will lead to a breakdown of the blood cells and vessels that carry the blood. This results in blood leaking from the vessels. Eventually, people bleed to death internally and die. Before controlled experiments were commonplace, a simple physician decided to tackle the problem of scurvy. James Lind, of the Royal Navy, came up with a simple controlled experiment to find the best cure for scurvy.

He separated sailors with scurvy into various groups. He subjected them to the same controlled condition and gave them the same diet, except one item. Each group was subjected to a different treatment or remedy, taken with their food. Some of these remedies included barley water, cider and a regiment of oranges and lemons. This created the first clinical trial , or test of the effectiveness of certain treatments in a controlled experiment. Lind found that the oranges and lemons helped the sailors recover fast, and within a few years the Royal Navy had developed protocols for growing small leafy greens that contained high amounts of vitamin C to feed their sailors.

Related Biology Terms

Field Experiment – An experiment conducted in nature, outside the bounds of total control.
Independent Variable – The thing in an experiment being changed or manipulated by the experimenter to see effects on the subject.
Controlled Variable – A thing that is normalized or standardized across an experiment, to remove it from having an effect on the subject being studied.
Control Group – A group of subjects in an experiment that receive no independent variable, or a normalized amount, to provide comparison.

1. Why is it necessary for scientist to conduct controlled experiments? A. They allow for more definite relationships of cause and effect to be established B. Without control, anything could happen in the experiment C. Safety first! Controls are just silly safety precautions

2. A population of birds is being studied. Which of the following describes a controlled experiment on the birds? A. The birds are subjected to a lighting strike, and the results observed. B. The birds are split in two groups, one left in the wild and one kept in captivity. After time, the effects are measured and compared. C. The birds are observed as they migrate from North to South America.

3. A scientist is interested in the effects of a pesticide on the eggs of certain birds. The scientist takes some eggs and coats them with pesticide, and does not coat a second group of eggs. He places them in an incubator for several days, then measures several chemical and physical properties of the eggs. Is this a good controlled experiment? A. Yes B. No C. Maybe, but there may be more to the picture

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Controlled Experiment | Definition & Example

Valerie has been teaching science for the last 15 years. She has experience teaching outdoor education, in science centers, science camps and in the classroom. She has engaged all levels of learners from preschool to adults. She has a Bachelor of science degree from Seattle Pacific University and a Masters in Teaching from Brandman. She also has a published science article and is scuba certified.

Sergey has a Masters in Biomedical Engineering and has taught science and mathematics courses at the University of Wisconsin-Madison.

What are the five components of a controlled experiment?

The five components of a controlled experiment are outlined in the scientific method: 1) defining the problem 2) making observations, 3) forming a hypothesis 4) conducting an experiment, and 5) drawing conclusions.

What is an example of a controlled experiment?

There are countless examples of controlled experiments. This experiment will walk through the scientific method and procedure of a controlled experiment. A scientist was stirring her coffee one day and noticed that her sugar dissolved quickly in her warm coffee. She then asked a question "I wonder if sugar dissolves more quickly in warm or cold water?" To design an experiment she would go into a lab setting to make sure she can control aspects of the air like temperature, humidity, and air movement, etc. Her dependent variable would be the temperature of the water and her independent variable would be the time it takes for the sugar to dissolve. She would set up 3 glasses of water: one at room temperature (the control), one hot water, and one cold water. She would then put 1 tablespoon of sugar into each cup and time how long it takes for the sugar to completely dissolve within the clear liquid. She would keep the number of stirs and pressure she stirs constantly. The only variable different within this experiment would be the temperature of the water. She would chart all of the information and run several trials of her experiment to ensure repeatability.

What is a controlled experiment in science?

A controlled experiment is defined as an experiment in which all the variable factors in an experimental group and a comparison control group are kept the same except for one variable factor in the experimental group that is changed or altered. A controlled experiment is a specific kind of scientific experiment where all aspects of the procedure are controlled except for the two variables that are being tested, the independent and dependent variables. The independent variable is the variable that is being manipulated or changed through the experiment (an example would be time) while the dependent variable is the direct change that happens in the experiment (an example would be the speed of a car). The scientific method is made up of steps to carry out testing a question.

How do you create a controlled experiment?

You create a controlled experiment by using a lab setting. This way you can physically control all aspects of the experiment except what you are testing. You need to use the scientific method to set up an observation, a hypothesis, procedure data, and conclusions.

What are some examples of controlled variables?

Probably one of the most famous controlled experiments was one done by Louis Pasteur. He wanted to answer the question: Can microorganisms generate spontaneously? Louis applied heat to a flask then let the flask sit for the same amount of time with the neck attached and with the neck detached and recorded if bacteria was present or not. Notice that Louis kept all the factors the same including the temperature, the wait time, and the kind of flask. He only changed one variable in the experiment and that was removing the neck of the flask to let air into it. The control in the experiment was to keep the neck attached and not let air into his sample. The variables he kept the same were the same type and size of meat, the amount of time he left the pieces out, and the same container used. The variable he changed was how exposed to the air the meat was.

What is a controlled experiment, variables in a controlled experiment, control group and experimental group, benefits of using controlled experiments, example of a controlled experiment, lesson summary.

A controlled experiment is defined as an experiment in which all the variable factors in an experimental group and a comparison control group are kept the same except for one variable factor in the experimental group that is changed or altered. A controlled experiment is a specific kind of scientific experiment where all aspects of the procedure are controlled except for the two variables that are being tested, the independent and dependent variables . The independent variable is the variable that is being manipulated or changed through the experiment (an example would be time) while the dependent variable is the direct change that happens in the experiment (an example would be the speed of a car). The scientific method is made up of steps to carry out testing a question. The steps are:

Ask a question
Research the topic
Develop a hypothesis
Test with an experiment
Analyze data
Report conclusions

Developing a controlled experiment is one way to test a hypothesis and is well accepted by the scientific community as reliable as the tests are controlled with few variables.

Famous Examples of Controlled Experiments

Another famous example of a controlled experiment was by Francesco Redi. He wanted to answer the question: Do maggots come from rotting meat? His experiment was simple but followed the controlled experiment setup. He put out two pieces of meat, one was covered and the other one wasn't. He noticed that unsealed meat had flies on it, but the sealed one did not, thus providing information about how to best store food before electricity was widely used.

Scientific Method: Brief Overview

The scientific method is a way for scientists to conduct experiments in a similar and reliable way. The method consists of steps that are easy to follow and replicate so that anyone in the scientific community can complete and follow the same experiment. The first step usually starts with observations and those observations turn into a testable question; however, the method can really start at any of the steps as long as they are all completed. After completing research on the topic, a hypothesis is formed. Then an experiment is developed and tested taking careful data. Analyzing the data is the next step to see if there was any difference between a control group and an experimental group . Then the conclusions are reported. Part of the scientific method is developing an experiment to answer a question. A controlled experiment that is repeatable is very important in this step. Scientists need to keep a record of their procedure and all of their data for the tests to be reliable. In a controlled experiment only one thing is changed at a time in order to increase the reliability of what is being tested.

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0:04 Controlled Experiment Defined
1:48 A Closer Look
2:35 Setting Up a…
3:13 Lesson Summary

In math, there are often variables that are trying to be solved or found. Variables in science are specific parts of an experiment that are being changed to test whether there is an outcome or not. For example, if a scientist was going to test the question: Do plants grow faster with sunlight? They would set up a controlled experiment where they could test this question. One plant would be in full sunlight, one plant in medium sunlight, and one plant would be out of the sunlight. The sunlight would be the only part of the experiment that is different, while everything else would stay the same. The scientist would control every other aspect of the experiment. The plants would be the same including the soil and the amount of water given. There are three main variables in an experiment and these are referred to as independent, dependent, and extraneous.

Independent Variable

An independent variable is a variable that is being manipulated or changed through the experiment. Within the controlled experiment, the hypothesis being tested will point at the independent variable. The example above about the amount of sunlight on plant growth would be an independent variable. Either the plant has sunlight, limited sunlight, or no sunlight, and this would be the independent variable. This is the variable that is tested and changed in the experiment to collect data and try to answer a question. A very common independent variable is time, and many studies change the amount of time in an experiment to discover if it has an effect on the dependent variable.

Dependent Variable

The dependent variable in an experiment is the direct change that happens due to changing the independent variable. In the example above about the amount of sunlight on plant growth, the dependent variable would be how much the plant grows in each environment. The dependent variable is where a scientist will gather the data and draw conclusions about what happened in the experiment.

Extraneous Variable

An extraneous variable in an experiment is any variable that the scientist isn't particularly investigating but could cause the outcome of the experiment to change. An example from the amount of sunlight and plant growth experiment could be the temperature difference of the plants in the different environments. The temperature of the plant locations could impact how much water is evaporated from the soil and could ultimately change how quickly or slowly the plant grows because of this. The experiment would try to eliminate the temperature difference but unless the plants were placed in a temperature-regulated, environment it could become an extraneous variable.

In an experiment, there are two groups including the control and the experimental groups . In the control group, the independent variable is not applied and it acts as something to compare the experimental group with. The control group gives a baseline for the experiment to take place and a starting place for data to be collected. Collecting data on both groups is essential so that they can be compared for similarities and differences. Ultimately in a controlled experiment, you are looking for a difference in data between the control group and experimental group because that will show that the experiment made a difference! The control group in the plant example would be the plant out of the sunlight because the experiment is specifically looking at whether or not plants grow better in the sunlight. The experimental group would be the plant in the sunlight; however, you can have any amount of experimental groups as long as there is a control to compare it to. By gathering data on both plants, the experiment would show a dramatic difference in plant growth. Both groups are extremely important to the success of an experiment and to the reliability of the data.

Methods of Control

In order to keep the integrity of control groups, there are some best practices that should be followed, usually random assignments, placebos , and multiple trials. Control groups are often used when testing a specific type of medicine or drug and looking for symptoms within the group. In order to keep the groups the same, the subjects in each group (humans, plants, or animals) would be randomly assigned to the control or experimental group and not told which one they were put in. Then both groups would be given a pill, the control group would be given a placebo pill and the experimental group would be given the actual medicine. Again, both groups wouldn't know what they are getting, scientists would then look for any symptoms over a certain period of time and be able to compare the control group to the experimental group.

In the science community, repetition is very important. An experiment should be able to be repeated by the same researcher many times over to ensure the same results and to eliminate any variables. The data should be consistent in the results and point to similar conclusions. In addition, the experiment should also be repeatable by other researchers following the same procedures to ensure similar results. Overall scientists need to keep copious notes on procedures, observations, and data to ensure its repeatability.

There are three main types of experiments: field experiments, natural experiments, and controlled experiments. Controlled experiments are mostly done in a lab where all aspects of the experiment can be controlled except for one variable that is being tested. Field experiments are done in natural environments where not all the variables can be controlled but are looking for real-world observations like viewing animals' behaviors in a natural environment. The last one is a natural experiment where a scientist who is studying a system asks a question or forms a hypothesis and then completes their research in a natural setting in which the variables are not controlled. The benefits of the controlled experiment are the reliability of the data and the repeatability of the experiments within the lab setting. It is also easier to distinguish which variable is contributing to a change in the experiment.

There are countless examples of controlled experiments. This experiment will walk through the scientific method and procedure of a controlled experiment. A scientist was stirring her coffee one day and noticed that her sugar dissolved quickly in her warm coffee. She then asked a question "I wonder if sugar dissolves more quickly in warm or cold water?" To design an experiment she would go into a lab setting to make sure she can control aspects of the air like temperature, humidity, and air movement. Her hypothesis is "If I put sugar in warm water, room temperature water, and cold water, then the warm water will dissolve the sugar more quickly than the other two." Her dependent variable would be the temperature of the water and her independent variable would be the time it takes for the sugar to dissolve. She would set up 3 glasses of water: one at room temperature (the control), one with hot water, and one with cold water. She would then put 1 tablespoon of sugar into each cup and time how long it takes for the sugar to completely dissolve within the clear liquid. She would keep the number of stirs and pressure she stirs constantly. The only variable different within this experiment would be the temperature of the water. She would chart all of the information and run several trials of her experiment to ensure repeatability.

All experiments in the scientific community follow the scientific method , to ensure repeatability and accuracy. There are three main types of experiments including controlled , field and natural experiments. Controlled experiments take into consideration all the variables of an experiment but only allow one to be changed at a time. There are three variables present in an experiment, the independent , dependent , and extraneous . The independent variable is the one in the experiment that is being tested or changed whereas the dependent variable depends on the outcome of the independent variable, and extraneous variables are oftentimes overlooked as they are parts of the experiment that could change the outcome unintentionally. An example of a controlled experiment is one done by Louis Pasteur where he was looking for the answer to the question of whether or not microorganisms generate spontaneously. In the experiment, he set out 3 pieces of meat, one open to the air, one with a vent, and one closed to air. He found that the first two generated flies while the last one did not. His conclusion was that the microorganisms had to have air in order to reproduce. We still use the concepts of this experiment today. This type of controlled experiment allows scientists the ability to repeat it many times to ensure the credibility of the results.

There are several methods and best practices of completing experiments that are important. One of the methods is to make sure the experiment is repeatable. Repetition is important because it allows anyone to follow a procedure to get the same results. This is for accuracy and for any other person to be able to complete the same experiment using detailed procedures and lab protocols. Another method is to make sure subjects in a controlled experiment are separated randomly into control and experimental groups . Researchers also need to ensure no bias is applied when conducting research and take copious notes to ensure it is accurate and repeatable. These details and methods are what allow a controlled experiment to be such an important experiment type.

Video Transcript

Controlled experiment defined.

Imagine conducting an experiment to evaluate the effectiveness of sleeping pills. You gather a group of test subjects and measure the average time it takes them to fall asleep after taking the pills. Afterwards, you measure the average time it takes these same test subjects to fall asleep without taking the pills. By comparing the results, can you make a valid scientific claim about effectiveness of the sleeping medication?

The answer is no, you can't. Why? Well, let's examine some arguments against the validity of such an experiment.

Each test subject has different life circumstances that could affect his or her tendency to fall asleep. For example, before taking the sleeping pills, a significant percentage of the test subjects might have been very tired from working extra hours at their jobs, making it easier for them to fall asleep. Or, for the second part of the experiment where they didn't take the pills, these test subjects might have been back to working regular hours. There also might have been a psychological effect on subjects' sleeping patterns because they believed the sleeping pills would help them fall asleep.

By conducting the experiment as previously described, we can't tell whether these and/or other factors influenced the results. To fix this issue, we need to make a controlled experiment in which the test subjects are divided among two or more groups, where at least one of these groups is a control group while the remaining are experimental groups. The control group is composed of test subjects who remain in their normal state for the duration of the experiment. For each experimental group , one variable is changed from the normal state. Let's take a closer look at what this means.

A Closer Look

In our example, the test subjects in the control group would continue living their normal lives, taking placebos (or 'fake' pills) to offset any type of psychological effect. That is, they would think they were on sleeping medication just like the test subjects in the experimental group, when in reality, they wouldn't be affected by the pills.

The remaining test subjects would be placed into one or more experimental groups. If we were interested in the effectiveness of one particular type of sleeping pill while all else remained constant, we'd only need one experimental group. But if there were other variables that we wanted to test, such as the efficacy of other sleeping medications, we would need more experimental groups. Now, let's look at setting up a controlled experiment.

Setting Up a Controlled Experiment

There are some important considerations in designing a controlled experiment. First, you need to determine what exactly is being tested and use this knowledge to create your experimental groups. In addition, you need to account for all the factors that could undesirably affect the results of your experiment.

For example, if you're testing the boiling point of water with and without salt being added to it, the elevation and ambient temperature at which the experiment is carried out can have an effect on the boiling temperature. Also, the water being tested should not have significant amounts of impurities in it.

A controlled experiment involves having a control group and one or more experimental groups. In the control group , the test subjects are kept in their normal state, while one variable under study is changed in each experimental group. Before setting up your controlled experiment, make sure to understand all the factors that could influence your results.

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Controlled Experiments | Methods & Examples of Control

Controlled Experiments | Methods & Examples of Control

Published on 19 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

Controlling variables can involve:

Holding variables at a constant or restricted level (e.g., keeping room temperature fixed)
Measuring variables to statistically control for them in your analyses
Balancing variables across your experiment through randomisation (e.g., using a random order of tasks)

Why does control matter in experiments, methods of control, problems with controlled experiments, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables.

Your independent variable is the colour used in advertising.
Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Design and description of the meal
Study environment (e.g., temperature or lighting)
Participant’s frequency of buying fast food
Participant’s familiarity with the specific fast food brand
Participant’s socioeconomic status

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You can control some variables by standardising your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., advert colour) should be systematically changed between groups.

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment, and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

A control group that’s presented with red advertisements for a fast food meal
An experimental group that’s presented with green advertisements for the same fast food meal

Random assignment

To avoid systematic differences between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a ‘true experiment’ – it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers – or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs.

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses. In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity – the extent to which your results can be generalised to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritise control or generalisability in your experiment.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

A testable hypothesis
One or more independent variables that you will manipulate
One or more dependent variables that you will measure

When designing the experiment, first decide:

How your variable(s) will be manipulated
How you will control for any potential confounding or lurking variables
How many subjects you will include
How you will assign treatments to your subjects

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Bhandari, P. (2022, October 10). Controlled Experiments | Methods & Examples of Control. Scribbr. Retrieved 9 June 2024, from https://www.scribbr.co.uk/research-methods/controlled-experiments/

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Pritha Bhandari

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Controlled Experiment

A controlled experiment is a scientific study where variables are carefully manipulated and controlled. It helps researchers establish cause-effect relationships.

In the realm of scientific research, controlled experiments hold significant importance for exploring and understanding various phenomena. By systematically adjusting and regulating specific variables, researchers can draw accurate conclusions and establish causal relationships. This methodical approach allows for the isolation of key factors influencing the outcomes, leading to reliable and reproducible results.

Through controlled experiments, scientists can unravel complex patterns, test hypotheses, and make informed decisions based on empirical evidence. In essence, controlled experiments serve as a cornerstone in the scientific method, providing a structured framework for inquiry and discovery.

Credit: www.simplypsychology.org

Designing A Controlled Experiment

In the process of conducting a controlled experiment, designing plays a pivotal role in setting the stage for accurate and reliable results. Each step of the design phase requires careful thought and attention to detail, as it ultimately dictates the validity of the entire experiment. From identifying the research question to formulating hypotheses and selecting variables, every aspect of the experiment’s design demands thorough consideration.

Identifying The Research Question

The first step in designing a controlled experiment is identifying the research question. This question serves as the foundation upon which the entire experiment is built. Ensuring that the research question is clear, specific, and measurable is essential to establishing a solid framework for the experiment.

Formulating The Hypothesis

After identifying the research question, the next step involves formulating the hypothesis. The hypothesis should clearly outline the relationship between the variables being studied and is vital in guiding the direction of the experiment.

Selecting The Variables

Upon formulating the hypothesis, selecting the variables to be studied is crucial. This process involves identifying and defining the independent and dependent variables, as well as any extraneous variables that could potentially impact the results.

Developing The Control Group

Another integral component of designing a controlled experiment is developing the control group. The control group serves as the baseline for comparison and allows researchers to isolate the effects of the independent variable on the dependent variable.

Randomization And Sample Size

Randomization and determining the appropriate sample size are critical aspects of experimental design. Random assignment helps minimize the influence of confounding variables, while a sufficient sample size ensures that the results are representative of the population being studied.

Conducting A Controlled Experiment

Define clear objectives and hypotheses for the experiment.
Create a detailed experimental plan with specific steps.
Apply the treatment to the experimental group as planned.
Ensure the control group receives no treatment for comparison.
Use reliable tools and methods to collect data accurately.
Record all data points meticulously for analysis.
Regularly check and adjust factors that could impact the experiment.
Keep conditions consistent across all groups throughout the experiment.
Document all observations in a structured format for analysis.
Ensure all researchers adhere to the observation recording procedure.

Analyzing And Interpreting Results

This study examines the controlled experiment on analyzing and interpreting results, providing valuable insights into the research process to drive decision-making. Discover how data analysis and interpretation play a crucial role in drawing meaningful conclusions and optimizing outcomes.

Data Analysis Techniques

In a controlled experiment, data analysis techniques play a crucial role.

Identifying Trends And Patterns

Identifying trends and patterns helps uncover valuable insights.

Drawing Conclusions

Drawing conclusions from the data leads to actionable outcomes.

Evaluating The Validity And Reliability

Ensuring the validity and reliability of results is essential.

Validation reinforces the credibility of the experiment.

Reliability ensures consistent and trustworthy outcomes.

Thorough analysis aids in assessing the experiment’s success.

Credit: www.khanacademy.org

Limitations And Considerations

In any controlled experiment, it is crucial to consider the limitations and various factors that may impact the study’s outcomes. Understanding potential biases, ethical considerations, generalizability and external validity, limitations of control groups, and addressing confounding variables are essential in ensuring the reliability and validity of the results.

Potential Biases

Potential biases, such as selection bias, measurement bias, or observer bias, can significantly affect the results of a controlled experiment. It’s important to identify and mitigate these biases to ensure the accuracy of the findings.

Ethical Considerations

Ethical considerations play a vital role in the planning and execution of a controlled experiment. It’s essential to uphold ethical standards, including informed consent, safeguarding participants’ privacy, and minimizing any potential harm or distress.

Generalizability And External Validity

Generalizability and external validity refer to the extent to which the findings of a controlled experiment can be applied to a broader population or real-world settings. It’s important to consider these factors to determine the practical implications of the study.

Limitations Of Control Groups

The limitations of control groups, such as ensuring they accurately represent the population being studied and minimizing the impact of variables, need to be carefully addressed to enhance the credibility of the experiment.

Addressing Confounding Variables

Identifying and addressing confounding variables is crucial in controlling for extraneous factors that could influence the outcomes of the experiment. Proper techniques, such as randomization and statistical controls, should be employed to minimize the impact of confounding variables.

Credit: explorebiology.org

Frequently Asked Questions Of Controlled Experiment

What is the meaning of controlled experiment.

A controlled experiment is a research method where variables are carefully controlled to measure the effects of one variable on another. It allows researchers to establish cause and effect relationships by eliminating confounding factors.

What Is An Example Of A Controlled Study?

An example of a controlled study is a clinical trial where participants are assigned to different groups, one receiving the treatment and the other a placebo. This helps to measure the effectiveness of the treatment while controlling for other variables.

What Is The Difference Between Controlled And Uncontrolled Experiments?

Controlled experiments involve manipulating variables, while uncontrolled experiments do not. Controlled experiments offer more reliable results due to the controlled conditions.

What Is A Controlled Cause To Effect Experiment?

In a controlled cause to effect experiment, variables are carefully manipulated to observe specific outcomes.

What Is A Controlled Experiment?

A controlled experiment is a scientific study where variables are carefully controlled to determine cause and effect.

To sum up, conducting controlled experiments is crucial for obtaining accurate and reliable results. By carefully controlling variables, researchers can better understand cause-and-effect relationships. This method enhances the credibility and applicability of scientific findings. As a result, controlled experiments play a vital role in advancing knowledge and innovation across various fields.

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Controlled Experiments: Definition, Steps, Results, Uses

Controlled experiments ensure valid and reliable results by minimizing biases and controlling variables effectively.

Rigorous planning, ethical considerations, and precise data analysis are vital for successful experiment execution and meaningful conclusions.

Real-world applications demonstrate the practical impact of controlled experiments, guiding informed decision-making in diverse domains.

Controlled experiments are the systematic research method where variables are intentionally manipulated and controlled to observe the effects of a particular phenomenon. It aims to isolate and measure the impact of specific variables, ensuring a more accurate causality assessment.

Table of Contents

Interesting Science Videos

Importance of controlled experiments in various fields

Controlled experiments are significant across diverse fields, including science, psychology, economics, healthcare, and technology.

They provide a systematic approach to test hypotheses, establish cause-and-effect relationships, and validate the effectiveness of interventions or solutions.

Why Controlled Experiments Matter?

Validity and reliability of results.

Controlled experiments uphold the gold standard for scientific validity and reliability. By meticulously controlling variables and conditions, researchers can attribute observed outcomes accurately to the independent variable being tested. This precision ensures that the findings can be replicated and are trustworthy.

Minimizing Biases and Confounding Variables

One of the core benefits of controlled experiments lies in their ability to minimize biases and confounding variables. Extraneous factors that could distort results are mitigated through careful control and randomization. This enables researchers to isolate the effects of the independent variable, leading to a more accurate understanding of causality.

Achieving Causal Inference

Controlled experiments provide a strong foundation for establishing causal relationships between variables. Researchers can confidently infer causation by manipulating specific variables and observing resulting changes. The capability informs decision-making, policy formulation, and advancements across various fields.

Planning a Controlled Experiment

Formulating research questions and hypotheses.

Formulating clear research questions and hypotheses is paramount at the outset of a controlled experiment. These inquiries guide the direction of the study, defining the variables of interest and setting the stage for structured experimentation.

Well-defined questions and hypotheses contribute to focused research and facilitate meaningful data collection.

Identifying Variables and Control Groups

Identifying and defining independent, dependent, and control variables is fundamental to experimental planning.

Precise identification ensures that the experiment is designed to isolate the effect of the independent variable while controlling for other influential factors. Establishing control groups allows for meaningful comparisons and robust analysis of the experimental outcomes.

Designing Experimental Procedures and Protocols

Careful design of experimental procedures and protocols is essential for a successful controlled experiment. The step involves outlining the methodology, data collection techniques, and the sequence of activities in the experiment.

A well-designed experiment is structured to maintain consistency, control, and accuracy throughout the study, thereby enhancing the validity and credibility of the results.

Conducting a Controlled Experiment

Randomization and participant selection.

Randomization is a critical step in ensuring the fairness and validity of a controlled experiment. It involves assigning participants to different experimental conditions in a random and unbiased manner.

The selection of participants should accurately represent the target population, enhancing the results’ generalizability.

Data Collection Methods and Instruments

Selecting appropriate data collection methods and instruments is pivotal in gathering accurate and relevant data. Researchers often employ surveys, observations, interviews, or specialized tools to record and measure the variables of interest.

The chosen methods should align with the experiment’s objectives and provide reliable data for analysis.

Monitoring and Maintaining Experimental Conditions

Maintaining consistent and controlled experimental conditions throughout the study is essential. Regular monitoring helps ensure that variables remain constant and uncontaminated, reducing the risk of confounding factors.

Rigorous monitoring protocols and timely adjustments are crucial for the accuracy and reliability of the experiment.

Analysing Results and Drawing Conclusions

Data analysis techniques.

Data analysis involves employing appropriate statistical and analytical techniques to process the collected data. This step helps derive meaningful insights, identify patterns, and draw valid conclusions.

Common techniques include regression analysis, t-tests , ANOVA , and more, tailored to the research design and data type .

Interpretation of Results

Interpreting the results entails understanding the statistical outcomes and their implications for the research objectives.

Researchers analyze patterns, trends, and relationships revealed by the data analysis to infer the experiment’s impact on the variables under study. Clear and accurate interpretation is crucial for deriving actionable insights.

Implications and Potential Applications

Identifying the broader implications and potential applications of the experiment’s results is fundamental. Researchers consider how the findings can inform decision-making, policy development, or further research.

Understanding the practical implications helps bridge the gap between theoretical insights and real-world application.

Common Challenges and Solutions

Addressing ethical considerations.

Ethical challenges in controlled experiments include ensuring informed consent, protecting participants’ privacy, and minimizing harm.

Solutions involve thorough ethics reviews, transparent communication with participants, and implementing safeguards to uphold ethical standards throughout the experiment.

Dealing with Sample Size and Statistical Power

The sample size is crucial for achieving statistically significant results. Adequate sample sizes enhance the experiment’s power to detect meaningful effects accurately.

Statistical power analysis guides researchers in determining the optimal sample size for the experiment, minimizing the risk of type I and II errors .

Mitigating Unforeseen Variables

Unforeseen variables can introduce bias and affect the experiment’s validity. Researchers employ meticulous planning and robust control measures to minimize the impact of unforeseen variables.

Pre-testing and pilot studies help identify potential confounders, allowing researchers to adapt the experiment accordingly.

A controlled experiment involves meticulous planning, precise execution, and insightful analysis. Adhering to ethical standards, optimizing sample size, and adapting to unforeseen variables are key challenges that require thoughtful solutions.

Real-world applications showcase the transformative potential of controlled experiments across varied domains, emphasizing their indispensable role in evidence-based decision-making and progress.

https://www.khanacademy.org/science/biology/intro-to-biology/science-of-biology/a/experiments-and-observations
https://www.scribbr.com/methodology/controlled-experiment/
https://link.springer.com/10.1007/978-1-4899-7687-1_891
http://ai.stanford.edu/~ronnyk/GuideControlledExperiments.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776925/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/
https://www.merriam-webster.com/dictionary/controlled%20experiment

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Krisha Karki

What is a Controlled Experiment?

In a scientific experiment, a controlled experiment is a test that is directly altered by the researcher so that only one variable is studied at a time. The single variable being studied will then be the independent variable.

This independent variable is manipulated by the researcher so that its effect on the hypothesis or data being studied is known. While the researcher studies the single independent variable, the controlled variables are made constant to reduce or balance out their impact on the research.

To achieve a controlled experiment, the research population is mostly distributed into two groups. Then the treatment is administered to one of the two groups, while the other group gets the control conditions. This other group is referred to as the control group.

The control group gets the standard conditions and is placed in the standard environment and it also allows for comparison with the other group, which is referred to as the experimental group or the treatment group. Obtaining the difference between these two groups’ behavior is important because in any scientific experiment, being able to show the statistical significance of the results is the only criterion for the results to be accepted.

So to determine whether the experiment supports the hypothesis, or if the data is a result of chance, the researcher will check for the difference between the control group and experimental group. Then the results from the differences will be compared with the expected difference.

For example, a researcher may want to answer this question, do dogs also have a music taste? In case you’re wondering too, yes, there are existing studies by researchers on how dogs react to different music genres.

Back to the example, the researcher may develop a controlled experiment with high consideration on the variables that affect each dog. Some of these variables that may have effects on the dog are; the dog’s environment when listening to music, the temperature of the environment, the music volume, and human presence.

The independent variable to focus on in this research is the genre of the music. To determine if there is an effect on the dog while listening to different kinds of music, the dog’s environment must be controlled. A controlled experiment would limit interaction between the dog and other variables.

In this experiment, the researcher can also divide the dogs into two groups, one group will perform the music test while the other, the control group will be used as the baseline or standard behavior. The control group behavior can be observed along with the treatment group and the differences in the two group’s behavior can be analyzed.

What is an Experimental Control?

Experimental control is the technique used by the researcher in scientific research to minimize the effects of extraneous variables. Experimental control also strengthens the ability of the independent variable to change the dependent variable.

For example, the cause and effect possibilities will be examined in a well-designed and properly controlled experiment if the independent variable (Treatment Y) causes a behavioral change in the dependent variable (Subject X).

In another example, a researcher feeds 20 lab rats with an artificial sweetener and from the researcher’s observation, six of the rats died of dehydration. Now, the actual cause of death may be artificial sweeteners or an unrelated factor. Such as the water supplied to the rats being contaminated or the rats could not drink enough, or suffering a disease.

Read: Nominal, Ordinal, Interval & Ratio Variable + [Examples]

For a researcher, eliminating these potential causes one after the other will consume time, and be tedious. Hence, the researcher can make use of experimental control. This method will allow the researcher to divide the rats into two groups: one group will receive the artificial sweetener while the other one doesn’t. The two groups will be placed in similar conditions and observed in similar ways. The differences that now occur in morbidity between the two groups can be traced to the sweetener with certainty.

From the example above, the experimental control is administered as a form of a control group. The data from the control group is then said to be the standard against which every other experimental outcome is measured.

Purpose & Importance of Control in Experimentation

1. One significant purpose of experimental controls is that it allows researchers to eliminate various confounding variables or uncertainty in their research. A researcher will need to use an experimental control to ensure that only the variables that are intended to change, are changed in research.

2. Controlled experiments also allow researchers to control the specific variables they think might have an effect on the outcomes of the study. The researcher will use a control group if he/she believes some extra variables can form an effect on the results of the study. This is to ensure that the extra variable is held constant and possible influences are measured.

3. Controlled experiments establish a standard that the outcome of a study should be compared to, and allow researchers to correct for potential errors.

Read more: What are Cross-Sectional Studies: Examples, Definition, Types

Methods of Experimental Control

Here are some methods used to achieve control in experimental research

Use of Control Groups

Control groups are required for controlled experiments. Control groups will allow the researcher to run a test on fake treatment, and comparable treatment. It will also compare the result of the comparison with the researcher’s experimental treatment. The results will allow the researcher to understand if the treatment administered caused the outcome or if other factors such as time, or others are involved and whether they would have yielded the same effects.

For an example of a control group experiment, a researcher conducting an experiment on the effects of colors in advertising, asked all the participants to come individually to a lab. In this lab, environmental conditions are kept the same all through the research.

For the researcher to determine the effect of colors in advertising, each of the participants is placed in either of the two groups: the control group or the experimental group.

In the control group, the advertisement color is yellow to represent the clothing industry while blue is given as the advertisement color to the experimental group to represent the clothing industry also. The only difference in these two groups will be the color of the advertisement, other variables will be similar.

Use of Masking (blinding)

Masking occurs in an experiment when the researcher hides condition assignments from the participants. If it’s double-blind research, both the researcher and the participants will be in the dark. Masking or blinding is mostly used in clinical studies to test new treatments.

Masking as a control measure takes place because sometimes, researchers may unintentionally influence the participants to act in ways that support their hypotheses. In another scenario, the goal of the study might be revealed to the participants through the study environment and this may influence their responses.

Masking, however, blinds the participants from having a deeper knowledge of the research whether they’re in the control group or the experimental group. This helps to control and reduce biases from either the researcher or the participants that could influence the results of the study.

Use of Random Assignment

Random assignment or distribution is used to avoid systematic differences between participants in the experimental group and the control group. This helps to evenly distribute extraneous participant variables, thereby making the comparison between groups valid. Another usefulness of random assignment is that it shows the difference between true experiments from quasi-experiments.

Learn About: Double-Blind Studies in Research: Types, Pros & Cons

How to Design a Controlled Experiment

For a researcher to design a controlled experiment, the researcher will need:

A hypothesis that can be tested.
One or more independent variables can be changed or manipulated precisely.
One or more dependent variables can be accurately measured.

Then, when the researcher is designing the experiment, he or she must decide on:

How will the variables be manipulated?
How will control be set up in case of any potential confounding variables?
How large will the samples or participants included in the study be?
How will the participants be distributed into treatment levels?

How you design your experimental control is highly significant to your experiment’s external and internal validity.

Controlled Experiment Examples

1. A good example of a controlled group would be an experiment to test the effects of a drug. The sample population would be divided into two, the group receiving the drug would be the experimental group while the group receiving the placebo would be the control group (Note that all the variables such as age, and sex, will be the same).

The only significant difference between the two groups will be the taking of medication. You can determine if the drug is effective or not if the control group and experimental group show similar results.

2. Let’s take a look at this example too. If a researcher wants to determine the impact of different soil types on the germination period of seeds, the researcher can proceed to set up four different pots. Each of the pots would be filled with a different type of soil and then seeds can be planted on the soil. After which each soil pot will be watered and exposed to sunlight.

The researcher will start to measure how long it took for the seeds to sprout in each of the different soil types. Control measures for this experiment might be to place some seeds in a pot without filling the pot with soil. The reason behind this control measure is to determine that no other factor is responsible for germination except the soil.

Here, the researcher can also control the amount of sun the seeds are exposed to, or how much water they are given. The aim is to eliminate all other variables that can affect how quickly the seeds sprouted.

Experimental controls are important, but it is also important to note that not all experiments should be controlled and It is still possible to get useful data from experiments that are not controlled.

Explore: 21 Chrome Extensions for Academic Researchers in 2021

Problems with Controlled Experiments

It is true that the best way to test for cause and effect relationships is by conducting controlled experiments. However, controlled experiments also have some challenges. Some of which are:

Difficulties in controlling all the variables especially when the participants in your research are human participants. It can be impossible to hold all the extra variables constant because all individuals have different experiences that may influence their behaviors.
Controlled experiments are at risk of low external validity because there’s a limit to how the results from the research can be extrapolated to a very large population .
Your research may lack relatability to real world experience if they are too controlled and that will make it hard for you to apply your outcomes outside a controlled setting.

Control Group vs an Experimental Group

There is a thin line between the control group and the experimental group. That line is the treatment condition. As we have earlier established, the experimental group is the one that gets the treatment while the control group is the placebo group.

All controlled experiments require control groups because control groups will allow you to compare treatments, and to test if there is no treatment while you compare the result with your experimental treatment.

Therefore, both the experimental group and the control group are required to conduct a controlled experiment

FAQs about Controlled Experiments

Is the control condition the same as the control group?

The control group is different from the control condition. However, the control condition is administered to the control group.

What are positive and negative control in an experiment?

The negative control is the group where no change or response is expected while the positive control is the group that receives the treatment with a certainty of a positive result.

While the controlled experiment is beneficial to eliminate extraneous variables in research and focus on the independent variable only to cause an effect on the dependent variable.

Researchers should be careful so they don’t lose real-life relatability to too controlled experiments and also, not all experiments should be controlled.

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What Is A Controlled Experiment? Aren’t All Experiments Controlled?

Why should you experiment, how should you experiment, key parameters of a controlled experiment, is there such a thing as an uncontrolled experiment.

A procedure that helps you understand the influence of various factors that affect a result and the extent of their effect in a controlled environment.

Have you ever done science experiments that have numerous parameters you need to take care of to get an accurate result?

If so, I know exactly how that feels!

Most of the time, you won’t get a perfect value, but rather a value that is nearly correct. It can be so frustrating at times, as you need to take care of the amount of catalyst, the temperature, pressure and a million other things!

I wonder who found out that you need precisely ‘this’ thing in exactly ‘this’ amount to get ‘that’ thing! Well, over time, I’ve realized just how much important these parameters are. These values help us set up a controlled environment where the experiment can occur.

And while many people loathe doing lengthy experiments, scientists have performed these exact same experiments a million times to find the perfect mix of parameters that give a predictable result! Now that’s perseverance!!

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Observation Method in Psychology: Naturalistic, Participant and Controlled

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.

Learn about our Editorial Process

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.

On This Page:

The observation method in psychology involves directly and systematically witnessing and recording measurable behaviors, actions, and responses in natural or contrived settings without attempting to intervene or manipulate what is being observed.

Used to describe phenomena, generate hypotheses, or validate self-reports, psychological observation can be either controlled or naturalistic with varying degrees of structure imposed by the researcher.

There are different types of observational methods, and distinctions need to be made between:

1. Controlled Observations 2. Naturalistic Observations 3. Participant Observations

In addition to the above categories, observations can also be either overt/disclosed (the participants know they are being studied) or covert/undisclosed (the researcher keeps their real identity a secret from the research subjects, acting as a genuine member of the group).

In general, conducting observational research is relatively inexpensive, but it remains highly time-consuming and resource-intensive in data processing and analysis.

The considerable investments needed in terms of coder time commitments for training, maintaining reliability, preventing drift, and coding complex dynamic interactions place practical barriers on observers with limited resources.

Controlled Observation

Controlled observation is a research method for studying behavior in a carefully controlled and structured environment.

The researcher sets specific conditions, variables, and procedures to systematically observe and measure behavior, allowing for greater control and comparison of different conditions or groups.

The researcher decides where the observation will occur, at what time, with which participants, and in what circumstances, and uses a standardized procedure. Participants are randomly allocated to each independent variable group.

Rather than writing a detailed description of all behavior observed, it is often easier to code behavior according to a previously agreed scale using a behavior schedule (i.e., conducting a structured observation).

The researcher systematically classifies the behavior they observe into distinct categories. Coding might involve numbers or letters to describe a characteristic or the use of a scale to measure behavior intensity.

The categories on the schedule are coded so that the data collected can be easily counted and turned into statistics.

For example, Mary Ainsworth used a behavior schedule to study how infants responded to brief periods of separation from their mothers. During the Strange Situation procedure, the infant’s interaction behaviors directed toward the mother were measured, e.g.,

Proximity and contact-seeking
Contact maintaining
Avoidance of proximity and contact
Resistance to contact and comforting

The observer noted down the behavior displayed during 15-second intervals and scored the behavior for intensity on a scale of 1 to 7.

Sometimes participants’ behavior is observed through a two-way mirror, or they are secretly filmed. Albert Bandura used this method to study aggression in children (the Bobo doll studies ).

A lot of research has been carried out in sleep laboratories as well. Here, electrodes are attached to the scalp of participants. What is observed are the changes in electrical activity in the brain during sleep ( the machine is called an EEG ).

Controlled observations are usually overt as the researcher explains the research aim to the group so the participants know they are being observed.

Controlled observations are also usually non-participant as the researcher avoids direct contact with the group and keeps a distance (e.g., observing behind a two-way mirror).

Controlled observations can be easily replicated by other researchers by using the same observation schedule. This means it is easy to test for reliability .
The data obtained from structured observations is easier and quicker to analyze as it is quantitative (i.e., numerical) – making this a less time-consuming method compared to naturalistic observations.
Controlled observations are fairly quick to conduct which means that many observations can take place within a short amount of time. This means a large sample can be obtained, resulting in the findings being representative and having the ability to be generalized to a large population.

Limitations

Controlled observations can lack validity due to the Hawthorne effect /demand characteristics. When participants know they are being watched, they may act differently.

Naturalistic Observation

Naturalistic observation is a research method in which the researcher studies behavior in its natural setting without intervention or manipulation.

It involves observing and recording behavior as it naturally occurs, providing insights into real-life behaviors and interactions in their natural context.

Naturalistic observation is a research method commonly used by psychologists and other social scientists.

This technique involves observing and studying the spontaneous behavior of participants in natural surroundings. The researcher simply records what they see in whatever way they can.

In unstructured observations, the researcher records all relevant behavior with a coding system. There may be too much to record, and the behaviors recorded may not necessarily be the most important, so the approach is usually used as a pilot study to see what type of behaviors would be recorded.

Compared with controlled observations, it is like the difference between studying wild animals in a zoo and studying them in their natural habitat.

With regard to human subjects, Margaret Mead used this method to research the way of life of different tribes living on islands in the South Pacific. Kathy Sylva used it to study children at play by observing their behavior in a playgroup in Oxfordshire.

Collecting Naturalistic Behavioral Data

Technological advances are enabling new, unobtrusive ways of collecting naturalistic behavioral data.

The Electronically Activated Recorder (EAR) is a digital recording device participants can wear to periodically sample ambient sounds, allowing representative sampling of daily experiences (Mehl et al., 2012).

Studies program EARs to record 30-50 second sound snippets multiple times per hour. Although coding the recordings requires extensive resources, EARs can capture spontaneous behaviors like arguments or laughter.

EARs minimize participant reactivity since sampling occurs outside of awareness. This reduces the Hawthorne effect, where people change behavior when observed.

The SenseCam is another wearable device that passively captures images documenting daily activities. Though primarily used in memory research currently (Smith et al., 2014), systematic sampling of environments and behaviors via the SenseCam could enable innovative psychological studies in the future.

By being able to observe the flow of behavior in its own setting, studies have greater ecological validity.
Like case studies , naturalistic observation is often used to generate new ideas. Because it gives the researcher the opportunity to study the total situation, it often suggests avenues of inquiry not thought of before.
The ability to capture actual behaviors as they unfold in real-time, analyze sequential patterns of interactions, measure base rates of behaviors, and examine socially undesirable or complex behaviors that people may not self-report accurately.
These observations are often conducted on a micro (small) scale and may lack a representative sample (biased in relation to age, gender, social class, or ethnicity). This may result in the findings lacking the ability to generalize to wider society.
Natural observations are less reliable as other variables cannot be controlled. This makes it difficult for another researcher to repeat the study in exactly the same way.
Highly time-consuming and resource-intensive during the data coding phase (e.g., training coders, maintaining inter-rater reliability, preventing judgment drift).
With observations, we do not have manipulations of variables (or control over extraneous variables), meaning cause-and-effect relationships cannot be established.

Participant Observation

Participant observation is a variant of the above (natural observations) but here, the researcher joins in and becomes part of the group they are studying to get a deeper insight into their lives.

If it were research on animals , we would now not only be studying them in their natural habitat but be living alongside them as well!

Leon Festinger used this approach in a famous study into a religious cult that believed that the end of the world was about to occur. He joined the cult and studied how they reacted when the prophecy did not come true.

Participant observations can be either covert or overt. Covert is where the study is carried out “undercover.” The researcher’s real identity and purpose are kept concealed from the group being studied.

The researcher takes a false identity and role, usually posing as a genuine member of the group.

On the other hand, overt is where the researcher reveals his or her true identity and purpose to the group and asks permission to observe.

It can be difficult to get time/privacy for recording. For example, researchers can’t take notes openly with covert observations as this would blow their cover. This means they must wait until they are alone and rely on their memory. This is a problem as they may forget details and are unlikely to remember direct quotations.
If the researcher becomes too involved, they may lose objectivity and become biased. There is always the danger that we will “see” what we expect (or want) to see. This problem is because they could selectively report information instead of noting everything they observe. Thus reducing the validity of their data.

Recording of Data

With controlled/structured observation studies, an important decision the researcher has to make is how to classify and record the data. Usually, this will involve a method of sampling.

In most coding systems, codes or ratings are made either per behavioral event or per specified time interval (Bakeman & Quera, 2011).

The three main sampling methods are:

Event-based coding involves identifying and segmenting interactions into meaningful events rather than timed units.

For example, parent-child interactions may be segmented into control or teaching events to code. Interval recording involves dividing interactions into fixed time intervals (e.g., 6-15 seconds) and coding behaviors within each interval (Bakeman & Quera, 2011).

Event recording allows counting event frequency and sequencing while also potentially capturing event duration through timed-event recording. This provides information on time spent on behaviors.

Coding Systems

The coding system should focus on behaviors, patterns, individual characteristics, or relationship qualities that are relevant to the theory guiding the study (Wampler & Harper, 2014).

Codes vary in how much inference is required, from concrete observable behaviors like frequency of eye contact to more abstract concepts like degree of rapport between a therapist and client (Hill & Lambert, 2004). More inference may reduce reliability.

Macroanalytic coding systems

Macroanalytic coding systems involve rating or summarizing behaviors using larger coding units and broader categories that reflect patterns across longer periods of interaction rather than coding small or discrete behavioral acts.

For example, a macroanalytic coding system may rate the overall degree of therapist warmth or level of client engagement globally for an entire therapy session, requiring the coders to summarize and infer these constructs across the interaction rather than coding smaller behavioral units.

These systems require observers to make more inferences (more time-consuming) but can better capture contextual factors, stability over time, and the interdependent nature of behaviors (Carlson & Grotevant, 1987).

Microanalytic coding systems

Microanalytic coding systems involve rating behaviors using smaller, more discrete coding units and categories.

For example, a microanalytic system may code each instance of eye contact or head nodding during a therapy session. These systems code specific, molecular behaviors as they occur moment-to-moment rather than summarizing actions over longer periods.

Microanalytic systems require less inference from coders and allow for analysis of behavioral contingencies and sequential interactions between therapist and client. However, they are more time-consuming and expensive to implement than macroanalytic approaches.

Mesoanalytic coding systems

Mesoanalytic coding systems attempt to balance macro- and micro-analytic approaches.

In contrast to macroanalytic systems that summarize behaviors in larger chunks, mesoanalytic systems use medium-sized coding units that target more specific behaviors or interaction sequences (Bakeman & Quera, 2017).

For example, a mesoanalytic system may code each instance of a particular type of therapist statement or client emotional expression. However, mesoanalytic systems still use larger units than microanalytic approaches coding every speech onset/offset.

The goal of balancing specificity and feasibility makes mesoanalytic systems well-suited for many research questions (Morris et al., 2014). Mesoanalytic codes can preserve some sequential information while remaining efficient enough for studies with adequate but limited resources.

For instance, a mesoanalytic couple interaction coding system could target key behavior patterns like validation sequences without coding turn-by-turn speech.

In this way, mesoanalytic coding allows reasonable reliability and specificity without requiring extensive training or observation. The mid-level focus offers a pragmatic compromise between depth and breadth in analyzing interactions.

Preventing Coder Drift

Coder drift results in a measurement error caused by gradual shifts in how observations get rated according to operational definitions, especially when behavioral codes are not clearly specified.

This type of error creeps in when coders fail to regularly review what precise observations constitute or do not constitute the behaviors being measured.

Preventing drift refers to taking active steps to maintain consistency and minimize changes or deviations in how coders rate or evaluate behaviors over time. Specifically, some key ways to prevent coder drift include:

Operationalize codes : It is essential that code definitions unambiguously distinguish what interactions represent instances of each coded behavior.
Ongoing training : Returning to those operational definitions through ongoing training serves to recalibrate coder interpretations and reinforce accurate recognition. Having regular “check-in” sessions where coders practice coding the same interactions allows monitoring that they continue applying codes reliably without gradual shifts in interpretation.
Using reference videos : Coders periodically coding the same “gold standard” reference videos anchors their judgments and calibrate against original training. Without periodic anchoring to original specifications, coder decisions tend to drift from initial measurement reliability.
Assessing inter-rater reliability : Statistical tracking that coders maintain high levels of agreement over the course of a study, not just at the start, flags any declines indicating drift. Sustaining inter-rater agreement requires mitigating this common tendency for observer judgment change during intensive, long-term coding tasks.
Recalibrating through discussion : Having meetings for coders to discuss disagreements openly explores reasons judgment shifts may be occurring over time. Consensus on the application of codes is restored.
Adjusting unclear codes : If reliability issues persist, revisiting and refining ambiguous code definitions or anchors can eliminate inconsistencies arising from coder confusion.

Essentially, the goal of preventing coder drift is maintaining standardization and minimizing unintentional biases that may slowly alter how observational data gets rated over periods of extensive coding.

Through the upkeep of skills, continuing calibration to benchmarks, and monitoring consistency, researchers can notice and correct for any creeping changes in coder decision-making over time.

Reducing Observer Bias

Observational research is prone to observer biases resulting from coders’ subjective perspectives shaping the interpretation of complex interactions (Burghardt et al., 2012). When coding, personal expectations may unconsciously influence judgments. However, rigorous methods exist to reduce such bias.

Coding Manual

A detailed coding manual minimizes subjectivity by clearly defining what behaviors and interaction dynamics observers should code (Bakeman & Quera, 2011).

High-quality manuals have strong theoretical and empirical grounding, laying out explicit coding procedures and providing rich behavioral examples to anchor code definitions (Lindahl, 2001).

Clear delineation of the frequency, intensity, duration, and type of behaviors constituting each code facilitates reliable judgments and reduces ambiguity for coders. Application risks inconsistency across raters without clarity on how codes translate to observable interaction.

Coder Training

Competent coders require both interpersonal perceptiveness and scientific rigor (Wampler & Harper, 2014). Training thoroughly reviews the theoretical basis for coded constructs and teaches the coding system itself.

Multiple “gold standard” criterion videos demonstrate code ranges that trainees independently apply. Coders then meet weekly to establish reliability of 80% or higher agreement both among themselves and with master criterion coding (Hill & Lambert, 2004).

Ongoing training manages coder drift over time. Revisions to unclear codes may also improve reliability. Both careful selection and investment in rigorous training increase quality control.

Blind Methods

To prevent bias, coders should remain unaware of specific study predictions or participant details (Burghardt et al., 2012). Separate data gathering versus coding teams helps maintain blinding.

Coders should be unaware of study details or participant identities that could bias coding (Burghardt et al., 2012).

Separate teams collecting data versus coding data can reduce bias.

In addition, scheduling procedures can prevent coders from rating data collected directly from participants with whom they have had personal contact. Maintaining coder independence and blinding enhances objectivity.

Bakeman, R., & Quera, V. (2017). Sequential analysis and observational methods for the behavioral sciences. Cambridge University Press.

Burghardt, G. M., Bartmess-LeVasseur, J. N., Browning, S. A., Morrison, K. E., Stec, C. L., Zachau, C. E., & Freeberg, T. M. (2012). Minimizing observer bias in behavioral studies: A review and recommendations. Ethology, 118 (6), 511-517.

Hill, C. E., & Lambert, M. J. (2004). Methodological issues in studying psychotherapy processes and outcomes. In M. J. Lambert (Ed.), Bergin and Garfield’s handbook of psychotherapy and behavior change (5th ed., pp. 84–135). Wiley.

Lindahl, K. M. (2001). Methodological issues in family observational research. In P. K. Kerig & K. M. Lindahl (Eds.), Family observational coding systems: Resources for systemic research (pp. 23–32). Lawrence Erlbaum Associates.

Mehl, M. R., Robbins, M. L., & Deters, F. G. (2012). Naturalistic observation of health-relevant social processes: The electronically activated recorder methodology in psychosomatics. Psychosomatic Medicine, 74 (4), 410–417.

Morris, A. S., Robinson, L. R., & Eisenberg, N. (2014). Applying a multimethod perspective to the study of developmental psychology. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (2nd ed., pp. 103–123). Cambridge University Press.

Smith, J. A., Maxwell, S. D., & Johnson, G. (2014). The microstructure of everyday life: Analyzing the complex choreography of daily routines through the automatic capture and processing of wearable sensor data. In B. K. Wiederhold & G. Riva (Eds.), Annual Review of Cybertherapy and Telemedicine 2014: Positive Change with Technology (Vol. 199, pp. 62-64). IOS Press.

Traniello, J. F., & Bakker, T. C. (2015). The integrative study of behavioral interactions across the sciences. In T. K. Shackelford & R. D. Hansen (Eds.), The evolution of sexuality (pp. 119-147). Springer.

Wampler, K. S., & Harper, A. (2014). Observational methods in couple and family assessment. In H. T. Reis & C. M. Judd (Eds.), Handbook of research methods in social and personality psychology (2nd ed., pp. 490–502). Cambridge University Press.

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What Is a Control Variable? Definition and Examples

A control variable is any factor that is controlled or held constant in an experiment.

A control variable is any factor that is controlled or held constant during an experiment . For this reason, it’s also known as a controlled variable or a constant variable. A single experiment may contain many control variables . Unlike the independent and dependent variables , control variables aren’t a part of the experiment, but they are important because they could affect the outcome. Take a look at the difference between a control variable and control group and see examples of control variables.

Importance of Control Variables

Remember, the independent variable is the one you change, the dependent variable is the one you measure in response to this change, and the control variables are any other factors you control or hold constant so that they can’t influence the experiment. Control variables are important because:

They make it easier to reproduce the experiment.
The increase confidence in the outcome of the experiment.

For example, if you conducted an experiment examining the effect of the color of light on plant growth, but you didn’t control temperature, it might affect the outcome. One light source might be hotter than the other, affecting plant growth. This could lead you to incorrectly accept or reject your hypothesis. As another example, say you did control the temperature. If you did not report this temperature in your “methods” section, another researcher might have trouble reproducing your results. What if you conducted your experiment at 15 °C. Would you expect the same results at 5 °C or 35 5 °C? Sometimes the potential effect of a control variable can lead to a new experiment!

Sometimes you think you have controlled everything except the independent variable, but still get strange results. This could be due to what is called a “ confounding variable .” Examples of confounding variables could be humidity, magnetism, and vibration. Sometimes you can identify a confounding variable and turn it into a control variable. Other times, confounding variables cannot be detected or controlled.

Control Variable vs Control Group

A control group is different from a control variable. You expose a control group to all the same conditions as the experimental group, except you change the independent variable in the experimental group. Both the control group and experimental group should have the same control variables.

Control Variable Examples

Anything you can measure or control that is not the independent variable or dependent variable has potential to be a control variable. Examples of common control variables include:

Duration of the experiment
Size and composition of containers
Temperature
Sample volume
Experimental technique
Chemical purity or manufacturer
Species (in biological experiments)

For example, consider an experiment testing whether a certain supplement affects cattle weight gain. The independent variable is the supplement, while the dependent variable is cattle weight. A typical control group would consist of cattle not given the supplement, while the cattle in the experimental group would receive the supplement. Examples of control variables in this experiment could include the age of the cattle, their breed, whether they are male or female, the amount of supplement, the way the supplement is administered, how often the supplement is administered, the type of feed given to the cattle, the temperature, the water supply, the time of year, and the method used to record weight. There may be other control variables, too. Sometimes you can’t actually control a control variable, but conditions should be the same for both the control and experimental groups. For example, if the cattle are free-range, weather might change from day to day, but both groups have the same experience. When you take data, be sure to record control variables along with the independent and dependent variable.

Box, George E.P.; Hunter, William G.; Hunter, J. Stuart (1978). Statistics for Experimenters : An Introduction to Design, Data Analysis, and Model Building . New York: Wiley. ISBN 978-0-471-09315-2.
Giri, Narayan C.; Das, M. N. (1979). Design and Analysis of Experiments . New York, N.Y: Wiley. ISBN 9780852269145.
Stigler, Stephen M. (November 1992). “A Historical View of Statistical Concepts in Psychology and Educational Research”. American Journal of Education . 101 (1): 60–70. doi: 10.1086/444032

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controlled experiment

Definition of controlled experiment

Word history.

1893, in the meaning defined above

Dictionary Entries Near controlled experiment

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Cite this Entry

“Controlled experiment.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/controlled%20experiment. Accessed 9 Jun. 2024.

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Science Fair Project Ideas for Kids, Middle & High School Students ⋅

Ideas for Controlled Variable Science Projects

Science Projects With Three Variables for Kids in Fifth Grade

Many science projects investigate a combination of independent and controlled variables to see what happens as a result - the dependent variable. To get reliable results from your experiments, you change the independent variables carefully and the controlled variables as little as possible; this ensures that only the things you're interested in affect your experimental results.

Does Sugar Dissolve More Quickly in Warm or Cool Water?

Heat a cup of water while allowing another cup of water to remain cool. Dissolve one teaspoon of sugar in each cup of water. The controlled variable would be the number of times and the pressure used to stir the mixture because added motion of the water may or may not dissolve the sugar more quickly whether the water is warm or cool. Record the amount of undissolved sugar in the bottom of the container.

Does a Plant Grow Better in Direct or Indirect Sunlight?

A science project involving plants has controlled variables in the amount of water given to each plant and the amount and kind of soil in which the plant is living. Place one plant in direct sunlight and the other in a shaded area or indoors to conduct the science experiment. Record daily results in the height of the plant.

Will a Baby Bunny Grow Bigger When Fed Rabbit Food or Fresh Vegetables?

Two rabbits, ideally from the same litter, can be used to conduct a classroom experiment. Give each rabbit a different diet: one of only fresh vegetables such as lettuce, carrots and celery; feed the other rabbit pellets from the pet store. The controlled variable in this experiment would be the weight in food each rabbit receives even though the type of food is different. Record the height, weight and length of the two rabbits each week.

Which Will Clean a Penny Faster, Water or Vinegar?

In two glass containers, place one cup of distilled water in one and white vinegar in the other. Carefully drop a dirty penny into each container of liquid and record the changes in the penny's appearance over the course of one week. The controlled variable is in the amount of liquid used to clean each penny.

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Scientific Method For Kids With Examples

Kids have questions about the world around them every day, and there is so much to learn through experimentation with simple materials. You can begin using the scientific method with elementary kids. Below we’ll share with you how and when to introduce the scientific method, the steps of the scientific method, and some easy scientific method experiments. There are so many great ways to enjoy science projects with kids!

how to use the scientific method with kids

What Is The Scientific Method?

The scientific method is a process or method of research. A problem is identified, information about the problem is gathered, a hypothesis or question is formulated from the information, and the hypothesis is put to the test with an experiment to prove or disprove its validity.

Sounds heavy… What in the world does that mean?!? It means you don’t need to try and solve the world’s biggest science questions! The scientific method is all about studying and learning things right around you.

As children develop practices that involve creating, gathering data evaluating, analyzing, and communicating, they can apply these critical thinking skills to any situation.

Note: The use of the best Science and Engineering Practices is also relevant to the topic of using the scientific method. Read more here and see if it fits your science planning needs.

Can Young Kids Use the Scientific Method?

Kids are great scientists at any age, and can use the scientific method in context to what they are learning. It can be adapted for any age!

The scientific method is a valuable tool for introducing kids to a logical way to solve scientific problems. Scientists use the scientific method to study, learn, and come up with an answer!

The scientific method is a process that helps double-check that answers are correct and the correct results are obtained through careful planning. Sometimes the guesses and questions change as you run your experiments.

Kids can use the scientific method too on questions that are relevant to them!

Let’s break the scientific method for kids down into six parts, and you can quickly see how each can be incorporated into your next science experiment.

What Are The Steps In The Scientific Method?

Make initial observations.
Come up with a question of interest that is based on the observations.
Develop a hypothesis or prediction to go along with the question.
Experiment and test.
Gather and record results of tests and experiments and draw conclusions.
Share and discuss results.

Whoa… Wait A Minute! That sounds like a lot for a young kid!

You are correct. Depending on your kid’s abilities, following all the scientific method steps precisely will not go well. Someone will get frustrated, bored, and turned off by just how cool science can be. We do not want that to happen!

Using The Scientific Method For Preschool and Kindergarten

Use the scientific method steps as a guideline in the back of your mind. You can cover most of the steps by talking with your kids about…

What do they think will happen?
What is happening ?
What happened compared to what they thought would happen ?

No writing is required! It’s also best to pick pretty straightforward ideas that aren’t overly involved or complicated to set up and test. Kids always have burning questions and “what ifs.”

See if you can tackle their next “what if” using the scientific method by listening carefully to their conversations. You can even have them keep a journal with their “what if” questions for your next science time.

Learn more about Science Activities For Preschoolers and Kindergarten Science Experiments .

Now on to how to apply the scientific method for elementary kiddos and beyond.

Scientific Method Steps In Action

Learn more about the steps of the scientific method below, which are great for science at home with your kids or in the classroom! We have also included some simple scientific method experiments for you to enjoy.

Ice Science Experiments are perfect for this! Try these 3 today !

STEP 1: Make Observations

Tons of everyday activities would make for cool science experiments using the scientific method. Listen to what your kids talk about and see happening. My son noticed that ice melted pretty fast in his water.

Observation is simply noticing what’s happening through our senses or with tools like a magnifying glass. Observation is used to collect and record data, enabling scientists to construct and test hypotheses and theories.

Learn more about observations in science.

STEP 2: Come Up With A Question

Your kids’ observations should lead to some sort of question. For my son and his ice observations, he came up with questions. Does ice melt faster in different liquids? His curiosity about what happens to the ice in liquids is a simple science experiment perfect for using the scientific method.

Next! Do some research and come up with ideas!

STEP 3: Develop A Prediction or Hypothesis

You have made your observations, you have your question, and now you need to make a prediction about what you think will happen.

A prediction is a guess at what might happen in an experiment based on observation or other information.

A hypothesis is not simply a guess! It’s a statement of what you believe will happen based on the information you have gathered.

My son hypothesizes that ice will melt faster in juice than in water.

STEP 4: Conduct An Experiment

We made a prediction that ice will melt faster in juice than it will in water, and now we have to test our hypothesis. We set up an experiment with a glass of juice, a glass of water, and an ice cube for each.

For the best experiments, only one thing should change! All the things that can be changed in a science experiment are called variables. There are three types of variables; independent, dependent, and controlled.

The independent variable is the one that is changed in the experiment and will affect the dependent variable. Here we will use different types of liquids to melt our ice cube in.

The dependent variable is the factor that is observed or measured in the experiment. This will be the melting of the ice cubes. Set up a stopwatch or set a time limit to observe the changes!

The controlled variable stays constant in the experiment. The liquids should be roughly the same temperature (as close as possible) for our ice melting experiment and measured to the same amount. So we left them out to come to room temperature. They could also be tested right out of the fridge!

You can find simple science experiments here with dependent and controlled variables.

STEP 5: Record Results and Draw Conclusions

Make sure to record what is happening as well as the results—note changes at specific time intervals or after one set time interval.

For example…

Record when each ice cube is completely melted.
Add drawings if you wish of the setup up and the end results.
Was your prediction accurate? If it was inaccurate, record why.
Write out a final conclusion to your experiment.

STEP 6: Communicate Your Results

This is the opportunity to talk about your hypothesis, experiment, results, and conclusion!

ALTERNATIVE IDEAS: Switch out an ice cube for a lollipop or change the liquids using vinegar and cooking oil.

Now you have gone through the steps of the scientific method, read on for more fun scientific method experiments to try!

Free printable scientific method worksheets!

Fun Scientific Method Experiments

Sink or float experiment.

A Sink or Float experiment is great for practicing the steps of the scientific method with younger kids.

Grab this FREE printable sink or float experiment

Here are a few of our favorite scientific method experiments, which are great for elementary-age kids . Of course, you can find tons more awesome and doable science projects for kids here!

Magic Milk Experiment

Start with demonstrating this delightful magic milk experiment. Then get kids to apply the steps of the scientific method by coming up with a question to investigate. What happens when you change the type of milk used?

What Dissolves In Water

Investigate what solids dissolve in water and what do not. Here’s a super fun science experiment for kids that’s very easy to set up! Learn about solutions, solutes, and solvents through experimenting with water and common kitchen ingredients.

Apple Browning Experiment

Investigate how to keep apples from turning brown with this apple oxidation experiment . What can you add to cut apples to stop or slow the oxidation process?

Freezing Water Experiment

Will it freeze? What happens to the freezing point of water when you add salt?

Viscosity Experiment

Learn about the viscosity of fluids with a simple viscosity experiment . Grab some marbles and add them to different household liquids to find out which one will fall to the bottom first.

Seed Germination Experiment

Set up a simple seed germination experiment .

Catapult Experiment

Make a simple popsicle stick catapult and use one of our experiment ideas to investigate from rubber band tension to changes in launch angle and more. How far can you fling your objects? Take measurements and find out.

Floating Orange

Investigate whether an orange floats or sinks in water, and what happens if you use different types of oranges. Learn about buoyancy and density with a simple ingredient from the kitchen, an orange.

Bread Mold Experiment

Grow mold on bread for science, and investigate how factors such as moisture, temperature, and air affect mold growth.

Eggshell Strength Experiment

Test how strong an egg is with this eggshell strength experiment . Grab some eggs, and find out how much weight an egg can support.

Free Printable Science Fair Starter Guide

Are you looking to plan a science fair project, make a science fair board, or want an easy guide to set up science experiments?

Learn more about prepping for a science fair and grab this free printable science fair project pack here!

If you want a variety of science fair experiments with instructions, make sure to pick up a copy of our Science Project Pack in the shop.

Bonus STEM Projects For Kids

STEM activities include science, technology, engineering, and mathematics. As well as our kids science experiments, we have lots of fun STEM activities for you to try. Check out these STEM ideas below…

Building Activities
Engineering Projects For Kids
What Is Engineering For Kids?
LEGO Engineering Projects
Coding Activities For Kids
STEM Worksheets
Top 10 STEM Challenges For Kids

Printable Science Projects Pack

If you’re looking to grab all of our printable science projects in one convenient place plus exclusive worksheets and bonuses like a STEAM Project pack, our Science Project Pack is what you need! Over 300+ Pages!

90+ classic science activities with journal pages, supply lists, set up and process, and science information. NEW! Activity-specific observation pages!
Best science practices posters and our original science method process folders for extra alternatives!
Be a Collector activities pack introduces kids to the world of making collections through the eyes of a scientist. What will they collect first?
Know the Words Science vocabulary pack includes flashcards, crosswords, and word searches that illuminate keywords in the experiments!
My science journal writing prompts explore what it means to be a scientist!!
Bonus STEAM Project Pack: Art meets science with doable projects!
Bonus Quick Grab Packs for Biology, Earth Science, Chemistry, and Physics

19 Comments

A great post and sure to help extend children’s thinking! I would like to download the 6 steps but the blue download button doesn’t seem to be working for me.

Thank you! All fixed. You should be able to download now!

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What Is a Controlled Experiment?
In an experiment, the control is a standard or baseline group not exposed to the experimental treatment or manipulation.It serves as a comparison group to the experimental group, which does receive the treatment or manipulation. The control group helps to account for other variables that might influence the outcome, allowing researchers to attribute differences in results more confidently to ...
What Is a Controlled Experiment?
Published on April 19, 2021 by Pritha Bhandari . Revised on June 22, 2023. In experiments, researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment, all variables other than the independent variable are controlled or held constant so they don't influence the dependent variable.
Controlled experiments (article)
There are two groups in the experiment, and they are identical except that one receives a treatment (water) while the other does not. The group that receives the treatment in an experiment (here, the watered pot) is called the experimental group, while the group that does not receive the treatment (here, the dry pot) is called the control group.The control group provides a baseline that lets ...
Controlled Experiments: Definition and Examples
A controlled experiment is a highly focused way of collecting data and is especially useful for determining patterns of cause and effect. This type of experiment is used in a wide variety of fields, including medical, psychological, and sociological research. Below, we'll define what controlled experiments are and provide some examples.
What Is a Controlled Experiment?
Controlled Experiment. A controlled experiment is simply an experiment in which all factors are held constant except for one: the independent variable. A common type of controlled experiment compares a control group against an experimental group. All variables are identical between the two groups except for the factor being tested.
Understanding Simple vs Controlled Experiments
Controlled Experiment . Controlled experiments have two groups of subjects. One group is the experimental group and it is exposed to your test. The other group is the control group, which is not exposed to the test.There are several methods of conducting a controlled experiment, but a simple controlled experiment is the most common. The simple controlled experiment has just the two groups: one ...
Controlled Experiment
Controlled Experiment Definition. A controlled experiment is a scientific test that is directly manipulated by a scientist, in order to test a single variable at a time. The variable being tested is the independent variable, and is adjusted to see the effects on the system being studied. The controlled variables are held constant to minimize or ...
Controlled Experiment
A controlled experiment is defined as an experiment in which all the variable factors in an experimental group and a comparison control group are kept the same except for one variable factor in ...
Controlled Experiments
Control in experiments is critical for internal validity, which allows you to establish a cause-and-effect relationship between variables. Example: Experiment. You're studying the effects of colours in advertising. You want to test whether using green for advertising fast food chains increases the value of their products.
Controlled Experiment
A controlled experiment is a scientific study where variables are carefully manipulated and controlled. It helps researchers establish cause-effect relationships. In the realm of scientific research, controlled experiments hold significant importance for exploring and understanding various phenomena.
Controlled Experiments: Definition, Steps, Results, Uses
Controlled Experiments: Definition, Steps, Results, Uses. Controlled experiments ensure valid and reliable results by minimizing biases and controlling variables effectively. Rigorous planning, ethical considerations, and precise data analysis are vital for successful experiment execution and meaningful conclusions.
Controlled Experiments: Methods, Examples & Limitations
Controlled Experiment Examples. 1. A good example of a controlled group would be an experiment to test the effects of a drug. The sample population would be divided into two, the group receiving the drug would be the experimental group while the group receiving the placebo would be the control group (Note that all the variables such as age, and ...
Biology: Controlled Experiments
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Experiment Definition in Science
In science, an experiment is a procedure that tests a hypothesis. In science, an experiment is simply a test of a hypothesis in the scientific method. It is a controlled examination of cause and effect. Here is a look at what a science experiment is (and is not), the key factors in an experiment, examples, and types of experiments.
Observational studies and experiments (article)
The researcher, to perform an expirement, would split the people into 2 groups. One would be taking the pill and one would be taking a fake pill. The fake pill is the control group, it is a baseline to limit the effect of confounding variables. The experimnet group would be the one to take the actual pill.
Controlled Experiment: Definition, Explanation And Example
A controlled experiment allows you to isolate and study the clear result that will eventually allow you to draw conclusions. A single phenomenon is the result of multiple factors, but how do you know the independent effect of each factor? A controlled experiment basically limits the scope of the result because only one or two factors affecting ...
Control Group Definition and Examples
A control group is not the same thing as a control variable. A control variable or controlled variable is any factor that is held constant during an experiment. Examples of common control variables include temperature, duration, and sample size. The control variables are the same for both the control and experimental groups.
Observation Methods: Naturalistic, Participant and Controlled
Controlled observations are also usually non-participant as the researcher avoids direct contact with the group and keeps a distance (e.g., observing behind a two-way mirror). Strengths. Controlled observations can be easily replicated by other researchers by using the same observation schedule. This means it is easy to test for reliability.
Scientific control
A scientific control is an experiment or observation designed to minimize the effects of variables other than the independent variable (i.e. confounding variables ). [1] This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the ...
What Is a Control Variable? Definition and Examples
Control Variable Examples. Anything you can measure or control that is not the independent variable or dependent variable has potential to be a control variable. Examples of common control variables include: Duration of the experiment. Size and composition of containers. Temperature.
Controlled experiment Definition & Meaning
The meaning of CONTROLLED EXPERIMENT is an experiment in which all the variable factors in an experimental group and a comparison control group are kept the same except for one variable factor in the experimental group that is changed or altered. How to use controlled experiment in a sentence.
Ideas for Controlled Variable Science Projects
A science project involving plants has controlled variables in the amount of water given to each plant and the amount and kind of soil in which the plant is living. Place one plant in direct sunlight and the other in a shaded area or indoors to conduct the science experiment. Record daily results in the height of the plant.
Scientific Method For Kids With Examples
For the best experiments, only one thing should change! All the things that can be changed in a science experiment are called variables. There are three types of variables; independent, dependent, and controlled. The independent variable is the one that is changed in the experiment and will affect the dependent variable. Here we will use ...
Microsoft Azure Blog
By Jessica Hawk Corporate Vice President, Data, AI, and Digital Applications, Product Marketing. Sharing insights on technology transformation along with important updates and resources about the data, AI, and digital application solutions that make Microsoft Azure the platform for the era of AI. Hybrid + Multicloud, Thought leadership.
Real Teenagers, Fake Nudes: The Rise of Deepfakes in American Schools
A disturbing new problem is sweeping American schools: Students are using artificial intelligence to create sexually explicit images of their classmates and then share them without the person ...

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Independent Variable

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Extraneous Variable

Methods of Control

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Control groups

Random assignment

Masking (blinding)

Difficult to control all variables

Risk of low external validity

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Controlled Experiment

Designing A Controlled Experiment

Identifying The Research Question

Formulating The Hypothesis

Selecting The Variables

Developing The Control Group

Randomization And Sample Size

Conducting A Controlled Experiment

Analyzing And Interpreting Results

Data Analysis Techniques

Identifying Trends And Patterns

Drawing Conclusions

Evaluating The Validity And Reliability

Limitations And Considerations

Potential Biases

Ethical Considerations

Generalizability And External Validity

Limitations Of Control Groups

Addressing Confounding Variables

Frequently Asked Questions Of Controlled Experiment