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What Is a Constant in the Scientific Method?

Can a Science Experiment Have Two Manipulated Variables?

The scientific method forms the foundation of the collective knowledge of the world around us. It is how researchers figure out what is likely true in nature. A scientific method experiment begins with a hypothesis, which is an informed opinion that explains why certain things occur the way they do. In science, hypotheses lead to predictions. These are measurable events that occur during an experiment if the hypothesis is true. The most significant components of the scientific method include hypotheses, dependent and independent variables, constant variables and control groups.

TL;DR (Too Long; Didn't Read)

A constant variable is an aspect of an experiment that a scientist or researcher keeps unchanged. There can be more than one constant in an experiment.

Through rigorous experimentation and corroboration, which requires other scientists to duplicate the same result as the first, a scientist's hypothesis is either confirmed or proven incorrect. While many people think of only men and women in white lab coats using the scientific method, it is an intuitive process. If you've ever asked yourself whether something is true or why something is the way it is—why is the sky blue?—you've performed the first step of the scientific method.

Why the Scientific Method Is Important

There is a good reason teachers introduce the scientific method early in a science class. It's the most important fundamental tool of science. Without the scientific method, there would be no way for scientists to agree on what is likely true and what is not.

The term "science" comes from the Latin word for "knowing." The scientific method is the process used to know that a new idea is valid. The confirmation of these new ideas has both theoretical and practical implications. For example, they can increase our knowledge of the universe and how it works. New ideas can lead to the development of inventions that change how people live.

There are three types of variables used in scientific experiments: constant, independent and dependent.

A constant variable is any aspect of an experiment that a researcher intentionally keeps unchanged throughout an experiment.

Experiments are always testing for measurable change, which is the dependent variable. You can also think of a dependent variable as the result obtained from an experiment. It is dependent on the change that occurs. Scientists introduce an independent variable to an experiment to create a change in the dependent variable. There can only be one independent variable in each experiment, but there will normally be many constant variables.

To illustrate a constant variable by looking at an example, let's say a new drug comes out that claims to make it easier to lose weight. Each scientific experiment can only focus on one independent variable or make one change at a time. If researchers gave a group of people this new drug and also increased the amount of exercise each person in the study did, it would complicate the picture. Scientists wouldn't be able to tell whether the pill or the exercise was responsible for any changes in weight, the dependent variable.

To ensure that only one independent variable exists, everything else is held constant. So, the constant variables in this experiment investigating the effects of the diet pill would be variables like the number of calories consumed by each participant, the amount of exercise they get, how much sleep they receive, etc. The constants are all the other aspects that are held the same for each participant.

Difference Between a Control and a Constant

You may think that a constant is the same thing as a control, but there is a difference. A control is specifically set aside without any changes to give the researcher an objective picture of any changes in the independent variable. For studies of drugs, a placebo is the control. A person is not told whether they're taking a diet pill or a placebo. A control negates the possible effects of persons believing they are taking diet pills when they are not.

When using the experimental method, it is critical to understand which variables are constants and which are controls. This helps to ensure any changes to the dependent variable are a result of the independent variable alone.

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About the Author

Amanda Cook holds a Bachelor of Science in Microbiology and a Doctorate in Health and Human Performance from Middle Tennessee State University. She has been writing online professionally since 2009.

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Biology archive

Course: biology archive   >   unit 1.

• The scientific method

Controlled experiments

• The scientific method and experimental design

Introduction

How are hypotheses tested.

• One pot of seeds gets watered every afternoon.
• The other pot of seeds doesn't get any water at all.

Control and experimental groups

Independent and dependent variables, independent variables, dependent variables, variability and repetition, controlled experiment case study: co 2 ‍   and coral bleaching.

• What your control and experimental groups would be
• What your independent and dependent variables would be
• What results you would predict in each group

Experimental setup

• Some corals were grown in tanks of normal seawater, which is not very acidic ( pH ‍   around 8.2 ‍   ). The corals in these tanks served as the control group .
• Other corals were grown in tanks of seawater that were more acidic than usual due to addition of CO 2 ‍   . One set of tanks was medium-acidity ( pH ‍   about 7.9 ‍   ), while another set was high-acidity ( pH ‍   about 7.65 ‍   ). Both the medium-acidity and high-acidity groups were experimental groups .
• In this experiment, the independent variable was the acidity ( pH ‍   ) of the seawater. The dependent variable was the degree of bleaching of the corals.
• The researchers used a large sample size and repeated their experiment. Each tank held 5 ‍   fragments of coral, and there were 5 ‍   identical tanks for each group (control, medium-acidity, and high-acidity). Note: None of these tanks was "acidic" on an absolute scale. That is, the pH ‍   values were all above the neutral pH ‍   of 7.0 ‍   . However, the two groups of experimental tanks were moderately and highly acidic to the corals , that is, relative to their natural habitat of plain seawater.

Analyzing the results

Non-experimental hypothesis tests, case study: coral bleaching and temperature, attribution:, works cited:.

• Hoegh-Guldberg, O. (1999). Climate change, coral bleaching, and the future of the world's coral reefs. Mar. Freshwater Res. , 50 , 839-866. Retrieved from www.reef.edu.au/climate/Hoegh-Guldberg%201999.pdf.
• Anthony, K. R. N., Kline, D. I., Diaz-Pulido, G., Dove, S., and Hoegh-Guldberg, O. (2008). Ocean acidification causes bleaching and productivity loss in coral reef builders. PNAS , 105 (45), 17442-17446. http://dx.doi.org/10.1073/pnas.0804478105 .
• University of California Museum of Paleontology. (2016). Misconceptions about science. In Understanding science . Retrieved from http://undsci.berkeley.edu/teaching/misconceptions.php .
• Hoegh-Guldberg, O. and Smith, G. J. (1989). The effect of sudden changes in temperature, light and salinity on the density and export of zooxanthellae from the reef corals Stylophora pistillata (Esper, 1797) and Seriatopora hystrix (Dana, 1846). J. Exp. Mar. Biol. Ecol. , 129 , 279-303. Retrieved from http://www.reef.edu.au/ohg/res-pic/HG%20papers/HG%20and%20Smith%201989%20BLEACH.pdf .

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Understanding Constants In An Experiment

• December 11, 2020
• Science Facts

Constants In An Experiment

The term ‘constant’ is used to refer to a particular quantity which is not intended to alter or change.

What are Constants?

Amongst the other fields, constants are also used in during various situations of an experiment. Such constants which are implemented in experiments are referred to as experimental constants.

Like other constants, experimental constants are also measurable. However, they cannot be changed in the due course of the experiment or in-between them.

There are various values which are considered as constants during experiments.

Constituents of natural forces such as the speed of light or the atomic weight of gold are considered as experimental constants.

Additionally, there are various properties which are considered to be experimental constants. The prime example of this is the boiling point of water.

The boiling point of water depends may alter depending on the altitude and the decrease in acceleration due to gravity.

However, experiments involving water in a single location consider its boiling point as constants.

The Need for Constants

There are various reasons why we need to implement constants within our experiments. However, they all stem out from the same characteristic, that is duplication of results or consistency in results.

Whenever we perform any experiment, we do so carefully ensuring that the process can be duplicated again as required.

If we involved a plethora of variables it would that we would receive a ton of variable results as well. This would completely defeat the purpose of experimenting.

Factors Considered as Constant in an Experiment

When we are on a lookout for constants, we essentially look for such factors which are considered to be similar in all states or conditions.

Irrespective of the time or the nature of this aforementioned factor, it will never change its state.

This stems out from the fact that a constant never changes its state in the duration of an experiment.

Understanding a constant becomes easier when one contrasts the constant factor with a mathematical constant.

In the field of mathematics, a constant refers to a particular factor which has a fixed numerical value.

In the same way, a constant in an experiment does not change its state and is universally equal all-around.

The only situation in which a mathematical constant and an experimental constant differ is that a mathematical constant does not involve any physical measurement.

Examples of Constants in Experiments

When you consider the factors used for determining an experimental constant, there are various constants that you might come across.

A few good examples of experimental constants include:

• The acceleration due to gravity
• Gravitational constant
• Avogadro’s constant
• The Gas constant
• Boltzmann’s constant
• The Stefan-Boltzmann constant
• Elementary charge
• Electron rest mass
• Proton rest mass
• Unified atomic mass unit
• Solar constant, and much more.

Apart from these constants, there are various other factors which are also considered as constants like Planck’s constant, the permittivity of free space, etc.

In essence, if you want to determine whether or not a particular factor is considered as a constant, you might want to think about such factors which contain a form of measurement that is universal.  

Constants In A Scientific Method

The term scientific method refers to an approach seeking a particular form of knowledge involving the formulation of a hypothesis or testing for proving its validity.

More often than not, scientific methods require intense experimentation for proving their validity. And such experiments often involve constants.

You might ask the purpose of constants in scientific methods. Here’s why we need them.

Whenever you need to perform experiments, you need to test through various factors which often involve a lot of measurable change.

These changes occur due to the presence of the dependent variable. As a result, the changes occurring allude to the dependent variable.

To understand such changes, the experimenters often introduce an independent variable for creating changes in the dependent variables.

However, there should always be only a single independent variable in such experiments.

Even other factors such as the presence of other variables are included in the form of controlled variables. And this is known as a constant in a scientific method.

Controls or Controlled Variables

Now, when you encounter the term ‘variable’, you might refer to such factors which are constantly found to be changing during an experiment. And you are right as well.

For the definition of a variable, states that any factor, trait, or condition which is found to exist in different amounts or types is a variable.

As a result, it would be correct to not refer to them as constants, right? Well, not exactly.

There are various situations in which variables are considered as constants. There are certain experiments in which a person performing the experiments considers certain variables in a constant state.

Such variables are referred to as controlled variables. As a result of this, the experimenter can attain more clarity in isolating the relationship between the independent variables and the dependent variables.

Moreover, by considering certain variables as constants, experimenters are also able to achieve constants results whenever they experiment.

The Prime Example of Controlled Variables

In the due course of an experiment, there are various variables which an experimenter considers to be constant.

The prime example of such controlled variables is the boiling point of water.

As aforementioned in the introductory paragraph, the boiling point of water variably changes when factors such as altitude and the acceleration due to gravity are involved in the experiment.

In spite of this, the temperature is considered constant as it allows the experimenter to derive constant results for a particular location or space.

Other Examples of Controlled Variables

Apart from the boiling point of water, there are various other examples which beautifully explain the concept of controlled variables within experiments.

A few of these include:

• The amount of fertilizer which a plant uses for the crop outgrowth.
• The type of soil is used for planting a particular type of plant.
• The amount of time which is spent by children in trying to learn a new concept.
• The amount of sunlight which a plant uses for its growth.

In spite of these examples, there are cases in which you might feel confused regarding controlled variables.

In simple terms, a controlled variable is referred to as determiners which greatly influence the result.

Usually, experimenters are more focused on understanding whether or not control variables have any significant effects on results.

With the help of control variables, they can do the same while achieving the desired results or outcomes in a particular experiment.

The Control Group

The term ‘control group’ essentially refers to a particular standard used for making comparisons in a particular experiment.

Whenever an experimenter stages an experiment, he or she designs it, particularly to include a control group and one or more experimental groups.

In an ideal sense, both the experimental groups and the control groups are similar.

However, the dissimilarity arises between these groups when the experimental group is subjected to various treatments which are believed to affect the outcome of the treatment.

Conversely, the control group isn’t subjected to any form of treatment or intervention which could affect the outcomes arising from the treatment.  

The Need For A Control Group

When you think about the involvement of a control group within the confinements of an experiment, you might think about the need which gives birth to such a need.

The primary reason why we need a control group is for the experimenters to easily be able to conclude a particular study.

It is only with the help of a control group that experimenters can determine whether or not a particular experiment can have a significant effect on the experimental group that can be recorded.

Moreover, the inclusion of a constant group within an experiment also ensures that the possibilities of making errors during the derivation of results are vastly minimized.

The Differences Between Constants and Controls

People often get confused with the different concepts that are involved with constants and controlled variables.

This is not only because they both begin with the same alphabet and that they sound the same, but it is also due to the similarity in their definitions.

However, you can be assured that these concepts don’t define the same things.

When we talk about constants, we essentially talk about the factors that are non-varying.

These factors are universally fixed and defined so that they are unable to start any changes that occur at the time of the results.

However, the purpose of control or a controlled variable isn’t the same.

Unlike a constant, a control or controlled variable is set aside to ignore the occurrence of any changes in the result that rise from the independent variable.

This ensures that the experimenter can view the experiment from an objective point of view.

When experimenters implement an experimental method, they do so understandingly which variables are controls and which of them are constants.

It is only by differentiating the controls and the constants that they can understand the changes occurring in the dependent variable.

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What Does ‘Constant’ Mean In Science?

Constants play a vital role across scientific disciplines by representing fixed, unchanging values. The fine structure constant in physics or the speed of light are examples of universal constants that remain the same under all conditions.

If you’re short on time, here’s a quick answer to your question: In science, a constant is a fixed, unchanging value or quantity that remains the same under specific conditions for a particular experiment or scenario .

In this detailed guide, we will explore the meaning of constants in science, provide examples from different fields, explain why they are important, and look at some well-known scientific constants used in equations and experiments.

Definition and Explanation of a Scientific Constant

In the realm of science, a constant refers to a value that remains unchanging and fixed. It is a fundamental concept that provides stability and reliability to scientific theories, experiments, and calculations.

Constants play a crucial role in the development of scientific laws, formulas, and calculations, as they allow scientists to make accurate predictions and draw meaningful conclusions.

Unchanging, fixed value

A scientific constant is a value that does not vary under normal circumstances. It remains consistent regardless of the conditions or variables involved. This stability allows scientists to establish a reliable baseline against which other measurements and observations can be compared.

For example, the speed of light in a vacuum, denoted by the symbol ‘c’, is considered a constant because it remains the same value, approximately 299,792,458 meters per second, regardless of the observer’s frame of reference.

Applies under defined conditions

Scientific constants apply within specific conditions or contexts. They are valid within a defined range of parameters, such as temperature, pressure, or composition. For instance, Avogadro’s constant, represented by ‘NA’, is a fundamental constant in chemistry that relates the number of atoms or molecules in a given amount of substance.

It is approximately equal to 6.022 x 10^23 particles per mole and is applicable in calculations involving gases and chemical reactions at standard temperature and pressure.

Used in scientific laws, formulas, and calculations

Scientific constants are utilized in the formulation of laws, formulas, and calculations in various scientific disciplines. They serve as building blocks for understanding and predicting natural phenomena.

For example, in physics, the gravitational constant ‘G’ is used in Newton’s law of universal gravitation to calculate the force of attraction between two objects. This constant allows scientists to accurately predict the motion of celestial bodies and explain phenomena such as planetary orbits and gravitational interactions.

It is important to note that scientific constants are not arbitrary values chosen by scientists. They are determined through extensive experimentation, observation, and mathematical analysis. These constants are often based on years, if not centuries, of research and are accepted within the scientific community as reliable and accurate representations of the natural world.

Examples of Famous Scientific Constants

In science, a constant is a value that does not change under specific conditions. Constants play a crucial role in various scientific theories and equations, providing a foundation for understanding the natural world. Here are some examples of famous scientific constants:

Speed of light (c)

The speed of light, denoted by the symbol ‘c’, is a fundamental constant in physics. It represents the maximum speed at which information or energy can travel in the universe. According to the current scientific understanding, the speed of light in a vacuum is approximately 299,792,458 meters per second.

Gravitational constant (G)

The gravitational constant, denoted by the symbol ‘G’, is a fundamental constant that characterizes the strength of the gravitational force between two objects. It plays a crucial role in Isaac Newton’s law of universal gravitation and Albert Einstein’s theory of general relativity.

The value of the gravitational constant is approximately 6.67430 x 10^-11 N(m/kg)^2.

Planck’s constant (h)

Planck’s constant, symbolized by ‘h’, is a fundamental constant in quantum mechanics. It relates the energy of a photon to its frequency and is used to calculate the energy levels of particles at the atomic and subatomic scale.

The value of Planck’s constant is approximately 6.62607015 x 10^-34 joule-seconds.

Gas constant (R)

The gas constant, denoted by the symbol ‘R’, is a universal constant that relates the properties of an ideal gas. It appears in the ideal gas law equation, which describes the behavior of gases under various conditions.

The value of the gas constant depends on the units used and is approximately 8.314 J/(mol·K).

Avogadro’s number

Avogadro’s number, denoted by ‘N A ‘, is a constant that represents the number of atoms or molecules in one mole of a substance. It is an essential constant in chemistry and is used to convert between the mass of a substance and the number of particles it contains.

The value of Avogadro’s number is approximately 6.02214076 x 10^23.

Universal constants in physics

Besides the examples mentioned above, there are several other universal constants in physics, such as the Boltzmann constant (k), the elementary charge (e), and the magnetic constant (μ 0 ). These constants have significant roles in various scientific disciplines and are used in a wide range of calculations and equations.

Mathematical constants like pi

In addition to the physical constants, there are also mathematical constants that hold a special place in science. One of the most famous mathematical constants is pi (π), which represents the ratio of the circumference of a circle to its diameter.

Pi is an irrational number, approximately equal to 3.14159, and it appears in numerous mathematical formulas and calculations.

These examples of famous scientific constants demonstrate the importance of constants in scientific research. They provide a solid foundation for understanding the laws of nature and enable scientists to make accurate predictions and calculations.

By using these constants, scientists can unlock the mysteries of the universe and push the boundaries of human knowledge.

Importance and Use of Scientific Constants

In the world of science, constants play a crucial role in understanding and explaining natural phenomena. These values remain fixed and unchanged, allowing scientists to make accurate calculations and draw meaningful conclusions.

Here are some key reasons why scientific constants are of utmost importance:

Allow precise quantitative analysis

Scientific constants provide a foundation for precise quantitative analysis. By having a known and consistent value, scientists can make accurate measurements and calculations in their experiments. This precision allows for more reliable and meaningful results.

For example, the speed of light, a fundamental constant in physics, enables scientists to calculate distances in space and time with great accuracy.

Enable the creation of scientific laws and formulas

Scientific constants are essential in the creation of scientific laws and formulas. These laws describe the relationships between different variables and constants, allowing scientists to make predictions and understand the underlying principles of nature.

For instance, Newton’s law of universal gravitation, which includes the gravitational constant, G, allows scientists to predict the gravitational force between two objects.

Support reproducibility in experiments

Reproducibility is a cornerstone of scientific research. Scientific constants contribute to the reproducibility of experiments by providing fixed reference points. With known constants, scientists can compare their results with those obtained by other researchers, ensuring that their findings are consistent and reliable.

This promotes transparency and helps to build upon previous knowledge. A well-known example is Avogadro’s constant, which allows scientists to determine the number of atoms or molecules in a given sample.

Provide fixed reference points

Scientific constants provide fixed reference points against which other measurements can be made. They serve as benchmarks that allow scientists to establish standardized units of measurement. For instance, the Planck constant, h, is a fundamental constant in quantum mechanics that defines the relationship between energy and frequency.

Its precise value provides a reference point for measuring the energy of particles and electromagnetic waves.

Allow measurement of other variables

Scientific constants enable the measurement of other variables that may be difficult to quantify directly. By incorporating known constants into equations, scientists can indirectly determine the values of various quantities.

This indirect measurement technique is often employed in fields like astrophysics and quantum mechanics. For example, the Boltzmann constant, k, allows scientists to determine the average kinetic energy of particles in a gas based on temperature.

Constants vs. Variables in Science Experiments

Constants remain fixed, variables can change.

In scientific experiments, constants and variables play crucial roles. A constant is a factor that remains unchanged throughout the entire experiment, while a variable is a factor that can be manipulated or changed.

Constants are carefully chosen to provide a stable and consistent baseline for comparison.

For example, imagine conducting an experiment to test the effect of temperature on the rate of a chemical reaction. In this case, the amount of reactants, the pressure, and the concentration of the solution would all be considered constants.

These variables are kept constant to ensure that any changes observed in the reaction rate can be attributed solely to the temperature.

Constants provide controls in experiments

Constants serve as controls in scientific experiments. By keeping certain factors constant, researchers can isolate the effects of the variable they are studying. This allows them to accurately determine the relationship between the variable and the observed results.

Continuing with the example of the temperature experiment, if the concentration of the solution were not kept constant, it could introduce confounding variables that would cloud the results. By controlling the concentration, researchers can confidently attribute any changes in the reaction rate solely to the temperature.

Changes in variables are measured against constants

Changes in variables are measured and compared against the constants in a scientific experiment. This comparison allows researchers to draw meaningful conclusions about the relationship between the variable and the outcomes.

Returning to the temperature experiment, the reaction rate at different temperatures would be measured and compared against the constant factors such as the concentration and pressure. By analyzing the data, researchers can determine how changes in temperature affect the rate of the chemical reaction.

Understanding the distinction between constants and variables is essential in scientific research. It ensures that experiments are conducted with precision and accuracy, allowing for reliable and reproducible results.

Establishing and Measuring Scientific Constants

In the field of science, constants play a crucial role in understanding and explaining the natural world. These constants are values that remain unchanged under specific conditions and are used as a foundation for scientific research and experimentation.

One such important aspect of establishing and measuring scientific constants is through high precision empirical measurements.

High precision empirical measurements

Scientists use advanced instruments and techniques to make precise measurements of physical quantities. These measurements are based on empirical evidence obtained through rigorous experimentation and observation.

By repeatedly measuring a specific phenomenon, scientists can establish the value of a constant with a high degree of accuracy. For example, the speed of light, denoted by the symbol ‘c,’ is a well-known constant that has been determined through meticulous measurements and experiments.

Consensus of scientific community

Scientific constants are not established arbitrarily; they require a consensus among the scientific community. When multiple researchers and scientists independently obtain similar results for a specific constant, it strengthens the reliability and validity of that value.

This consensus is crucial in ensuring the accuracy and credibility of scientific constants. It also allows scientists to build upon existing knowledge and theories, leading to further advancements in their respective fields.

Technological advances enabling greater accuracy

Technological advancements have played a significant role in enabling scientists to measure constants with greater precision. Improved instruments, such as atomic clocks and particle detectors, have revolutionized the way scientists can measure and understand the physical world.

These technological advancements have allowed for the refinement of existing constants and the discovery of new ones. For instance, advancements in quantum mechanics have led to the establishment of the Planck constant, which plays a fundamental role in understanding the behavior of subatomic particles.

Importance of exact, standardized values

Exact and standardized values of constants are of paramount importance in scientific research and development. They provide a common language for scientists to communicate and collaborate effectively. Standardized values allow for consistency and reproducibility in experiments, ensuring that results obtained by different researchers are comparable.

This is essential for advancing scientific knowledge and developing practical applications. For example, the value of the gravitational constant, denoted by ‘G’, is crucial in various fields, including astrophysics and engineering, where accurate calculations and predictions are required.

Establishing and measuring scientific constants is a meticulous process that combines empirical evidence, consensus among the scientific community, and technological advancements. These constants serve as the building blocks of scientific knowledge, enabling researchers to understand the natural world and make significant advancements in various fields.

They provide a solid foundation for scientific theories and practical applications, contributing to the progress of society as a whole.

Constants serve an important role in science by representing fixed, known values that remain unchanged under defined conditions. They enable quantitative analysis, precise formulas and reproducible experiments.

Famous constants like the speed of light, gravitational constant and Planck’s constant are fundamental to physics and other areas of science. Understanding what constants represent and how they are established, measured and used is key for scientific learning.

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Experimental Design - Independent, Dependent, and Controlled Variables

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Scientific experiments are meant to show cause and effect of a phenomena (relationships in nature).  The “ variables ” are any factor, trait, or condition that can be changed in the experiment and that can have an effect on the outcome of the experiment.

An experiment can have three kinds of variables: i ndependent, dependent, and controlled .

• The independent variable is one single factor that is changed by the scientist followed by observation to watch for changes. It is important that there is just one independent variable, so that results are not confusing.
• The dependent variable is the factor that changes as a result of the change to the independent variable.
• The controlled variables (or constant variables) are factors that the scientist wants to remain constant if the experiment is to show accurate results. To be able to measure results, each of the variables must be able to be measured.

For example, let’s design an experiment with two plants sitting in the sun side by side. The controlled variables (or constants) are that at the beginning of the experiment, the plants are the same size, get the same amount of sunlight, experience the same ambient temperature and are in the same amount and consistency of soil (the weight of the soil and container should be measured before the plants are added). The independent variable is that one plant is getting watered (1 cup of water) every day and one plant is getting watered (1 cup of water) once a week. The dependent variables are the changes in the two plants that the scientist observes over time.

Can you describe the dependent variable that may result from this experiment? After four weeks, the dependent variable may be that one plant is taller, heavier and more developed than the other. These results can be recorded and graphed by measuring and comparing both plants’ height, weight (removing the weight of the soil and container recorded beforehand) and a comparison of observable foliage.

Using What You Learned: Design another experiment using the two plants, but change the independent variable. Can you describe the dependent variable that may result from this new experiment?

Think of another simple experiment and name the independent, dependent, and controlled variables. Use the graphic organizer included in the PDF below to organize your experiment's variables.

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Home » Control Variable – Definition, Types and Examples

Control Variable – Definition, Types and Examples

Table of Contents

Control Variable

Definition :

Control variable, also known as a “constant variable,” is a variable that is held constant or fixed during an experiment or study to prevent it from affecting the outcome. In other words, a control variable is a variable that is kept the same or held constant to isolate the effects of the independent variable on the dependent variable.

For example, if you were conducting an experiment to test how temperature affects plant growth, you might want to control variables such as the amount of water, the amount of sunlight, and the type of soil to ensure that these variables do not interfere with the results. By controlling these variables, you can isolate the effect of temperature on plant growth and draw more accurate conclusions from the experiment.

Types of Control Variables

Types of Control Variables are as follows:

Environmental Control Variables

These are variables related to the physical environment in which the experiment is conducted, such as temperature, humidity, light, and sound.

Participant Control Variables

These are variables related to the participants in the experiment, such as age, gender, prior knowledge, or experience.

Experimental Control Variables

These are variables that the researcher manipulates or controls to ensure that they do not affect the outcome of the experiment. For example, in a study on the effects of a new medication, the researcher might control the dosage, frequency, or duration of the treatment.

Procedural Control Variables

These are variables related to the procedures or methods used in the experiment, such as the order in which tasks are completed, the timing of measurements, or the instructions given to participants.

Equipment Control Variables

These are variables related to the equipment or instruments used in the experiment, such as calibration, maintenance, or proper functioning.

How to Control a Variable

To control a variable in a scientific experiment, you need to ensure that it is kept constant or unchanged throughout the experiment. Here are some steps to help you control a variable:

Identify the Variable

Start by identifying the variable that you want to control. This can be an environmental, subject, procedural, or instrumentation variable.

Determine the Level of Control Needed

Depending on the variable, you may need to exert varying levels of control. For example, environmental variables may require you to control the temperature, humidity, and lighting in your experiment, while subject variables may require you to select a specific group of participants that meet certain criteria.

Establish a Standard Level

Determine the standard level or value of the variable that you want to control. For example, if you are controlling the temperature, you may set the temperature to a specific degree and ensure that it is maintained at that level throughout the experiment.

Monitor the Variable

Throughout the experiment, monitor the variable to ensure that it remains constant. Use appropriate equipment or instruments to measure the variable and make adjustments as necessary to maintain the desired level.

Document the Process

Document the process of controlling the variable to ensure that the experiment is replicable. This includes documenting the standard level, monitoring procedures, and any adjustments made during the experiment.

Examples of Control Variables

Here are some examples of control variables in Scientific Experiments and Research:

• Environmental Control Variables Example: Suppose you are conducting an experiment to study the effect of light on plant growth. You would want to control environmental factors such as temperature, humidity, and soil nutrients. In this case, you might keep the temperature and humidity constant and use the same type and amount of soil for all the plants.
• Subject Control Variables Example : If you are conducting an experiment to study the effect of a new medication on blood pressure, you would want to control subject variables such as age, gender, and health status. In this case, you might select a group of participants with similar ages, genders, and health conditions to ensure that these variables do not affect the results.
• Procedural Control Variables Example : Suppose you are conducting an experiment to study the effect of distraction on reaction time. You would want to control procedural variables such as the time of day, the order of the tasks, and the instructions given to the participants. In this case, you might ensure that all participants perform the tasks in the same order, at the same time of day, and receive the same instructions.
• Instrumentation Control Variables Example : If you are conducting an experiment to study the effect of a new measurement device on the accuracy of readings, you would want to control instrumentation variables such as the type and calibration of the device. In this case, you might use the same type and model of the device and ensure that it is calibrated before each use.

Applications of Control Variable

Control variables are widely used in scientific research across various fields, including physics, biology, psychology, and engineering. Here are some applications of control variables:

• In medical research , control variables are used to ensure that any observed effects of a new treatment or medication are due to the treatment and not some other variable. By controlling subject variables such as age, gender, and health status, researchers can isolate the effects of the treatment and determine its effectiveness.
• In environmental research , control variables are used to study the effects of changes in the environment on various species or ecosystems. By controlling environmental variables such as temperature, humidity, and lighting, researchers can determine how different species adapt to changes in the environment.
• In psychology research, control variables are used to study the effects of different interventions or therapies on cognitive or behavioral outcomes. By controlling procedural variables such as the order of tasks, the length of time allotted for each task, and the instructions given to participants, researchers can isolate the effects of the intervention and determine its effectiveness.
• In engineering research, control variables are used to study the effects of different design parameters on the performance of a system or device. By controlling instrumentation variables such as the type of measurement device used and the calibration of instruments, researchers can ensure that the measurements are accurate and reliable.

Purpose of Control Variable

The purpose of a control variable in an experiment is to ensure that any observed changes or effects are a result of the manipulation of the independent variable and not some other variable. By keeping certain variables constant, researchers can isolate the effects of the independent variable and determine whether it has a significant effect on the dependent variable.

Control variables are important because they help to increase the reliability and validity of the experiment. Reliability refers to the consistency and reproducibility of the results, while validity refers to the accuracy and truthfulness of the results. By controlling variables, researchers can reduce the potential for extraneous or confounding variables that can affect the outcome of the experiment and increase the likelihood that the results accurately reflect the effect of the independent variable on the dependent variable.

Characteristics of Control Variable

Control variables have the following characteristics:

• Constant : Control variables are kept constant or unchanged throughout the experiment. This means that their values do not vary or change during the experiment. Keeping control variables constant helps to ensure that any observed effects or changes are due to the manipulation of the independent variable and not some other variable.
• Independent : Control variables are independent of the independent variable being studied. This means that they do not affect the relationship between the independent and dependent variables. By controlling for independent variables, researchers can isolate the effect of the independent variable and determine its impact on the dependent variable.
• Documented: Control variables are documented in the experiment. This means that their values and methods of control are recorded and reported in the results section of the research paper. By documenting control variables, researchers can demonstrate the rigor and transparency of their study and allow other researchers to replicate their methods.
• Relevant: Control variables are relevant to the research question. This means that they are chosen based on their potential to affect the outcome of the experiment. By selecting relevant control variables, researchers can reduce the potential for extraneous or confounding variables that can affect the outcome of the experiment and increase the reliability and validity of the results.
• Varied : Control variables can be varied across different conditions or groups. This means that different levels of control may be needed depending on the research question or hypothesis being tested. By varying control variables, researchers can test different hypotheses and determine the factors that affect the outcome of the experiment.

Advantages of Control Variable

The advantages of using control variables in an experiment are:

• Increased accuracy : Control variables help to increase the accuracy of the results by reducing the potential for extraneous or confounding variables that can affect the outcome of the experiment. By controlling for these variables, researchers can isolate the effect of the independent variable on the dependent variable and determine whether it has a significant impact.
• Increased reliability : Control variables help to increase the reliability of the results by reducing the variability in the experiment. By keeping certain variables constant, researchers can ensure that any observed changes or effects are due to the manipulation of the independent variable and not some other variable.
• Reproducibility: Control variables help to increase the reproducibility of the results by ensuring that the same results can be obtained when the experiment is repeated. By documenting and reporting control variables, researchers can demonstrate the rigor and transparency of their study and allow other researchers to replicate their methods.
• Generalizability : Control variables help to increase the generalizability of the results by reducing the potential for bias and increasing the external validity of the experiment. By controlling for relevant variables, researchers can ensure that their findings are applicable to a broader population or context.
• Causality : Control variables help to establish causality by ensuring that any observed changes or effects are due to the manipulation of the independent variable and not some other variable. By controlling for confounding variables, researchers can increase the internal validity of the experiment and establish a cause-and-effect relationship between the independent and dependent variables.

Disadvantages of Control Variable

There are some potential disadvantages or limitations of using control variables in an experiment:

• Complexity : Controlling for multiple variables can make an experiment more complex and time-consuming. This can increase the likelihood of errors and reduce the feasibility of the experiment, especially if the control variables require a lot of resources or are difficult to measure.
• Artificiality : Controlling for variables can make the experimental conditions artificial and not reflective of real-world situations. This can reduce the external validity of the experiment and limit the generalizability of the findings to real-world settings.
• Limited scope : Controlling for specific variables can limit the scope of the experiment and make it difficult to generalize the results to other situations or populations. This can reduce the external validity of the experiment and limit its practical applications.
• Assumptions: Controlling for variables requires making assumptions about which variables are relevant and how they should be controlled. These assumptions may not be valid or accurate, and the results of the experiment may be affected by uncontrolled variables that were not considered.
• Cost : Controlling for variables can be costly, especially if the control variables require additional resources or equipment. This can limit the feasibility of the experiment, especially for researchers with limited funding or resources.

Limitations of Control Variable

There are several limitations of using control variables in an experiment, including:

• Not all variables can be controlled : There may be some variables that cannot be controlled or manipulated in an experiment. For example, some variables may be too difficult or expensive to measure or control, or they may be affected by factors outside of the researcher’s control.
• Interaction effects : Control variables can interact with each other, which can lead to unexpected results. For example, controlling for one variable may have a different effect when another variable is also controlled, or when the two variables interact with each other. These interaction effects can be difficult to predict or control for.
• Over-reliance on statistical significance: Controlling for variables can increase the statistical significance of the results, but this may not always translate to practical significance or real-world significance. Researchers should interpret the results of an experiment in light of the practical significance, not just the statistical significance.
• Limited generalizability : Controlling for variables can limit the generalizability of the results to other populations or situations. If the control variables are not representative of other populations or situations, the results of the experiment may not be applicable to those contexts.
• May mask important effects : Controlling for variables can mask important effects that are related to the independent variable. By controlling for certain variables, researchers may miss important interactions between the independent variable and the controlled variable, which can limit the understanding of the causal relationship between the two.

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What is a Constant in a Science Experiment? Exploring Its Role, Benefits, and Examples

By Happy Sharer

Introduction

The term “constant” has a specific meaning in the context of scientific experiments. In general, a constant is defined as any factor that remains unchanged throughout the duration of the experiment. Constants play a key role in any scientific research and can have a significant impact on the accuracy and validity of the results. It is therefore essential for scientists to identify and control constants in order to ensure reliable experimental results.

Analyzing the Role of Constants in Scientific Experiments

In a science experiment, constants are used to maintain consistency within the experiment. By ensuring that certain factors remain the same, scientists are able to measure the effects of independent variables on the dependent variable, or the outcome of the experiment. For example, if a scientist is conducting an experiment to measure the effect of light intensity on plant growth, they would need to ensure that all other environmental factors such as temperature, soil composition, and water levels remain consistent throughout the experiment. This allows the scientist to accurately measure the effects of the independent variable (light intensity) on the dependent variable (plant growth).

Constants also help to eliminate potential sources of error in an experiment. By controlling the constants, scientists are able to reduce the number of variables that could potentially affect the outcome of the experiment and thus increase the accuracy of the results. According to Dr. David M. Buss, a professor at the University of Texas at Austin, “By eliminating extraneous variables, constants help to provide more accurate results and conclusions from the experiment.”

Examining How to Identify and Control Variables and Constants in Science Experiments

Identifying and controlling constants in a science experiment can be a difficult but necessary task. The first step is to recognize the difference between a constant and a variable. A variable is any factor that can be changed or manipulated during the course of an experiment, while a constant is a factor that must remain unchanged. Once the variables and constants have been identified, scientists can then begin the process of controlling them.

One way to control constants is to standardize conditions within the experiment. This involves keeping the environment, equipment, and procedure consistent throughout the experiment. For example, if a scientist is conducting an experiment on the effects of temperature on seed germination, they would need to make sure that the amount of water, light, and air flow remain the same for each trial. This helps to ensure that the results are not affected by any outside factors. Additionally, scientists should use the same set of materials and equipment for each trial to avoid any potential sources of bias or variability.

Discussing the Benefits of Using Constants in Science Experiments

Using constants in science experiments can be extremely beneficial. One of the main advantages of using constants is that it helps to improve the accuracy of the results. By controlling the constants, scientists can reduce the number of potential sources of error and thus increase the reliability of the data. Additionally, using constants also helps to ensure consistency within the experiment, which makes it easier for scientists to compare results across different trials.

Furthermore, using constants can also help to improve the validity of the results. According to Dr. Richard L. Sorensen, a professor of biology at the University of Wisconsin-Madison, “By controlling the constants, scientists can ensure that the results of their experiments are valid and can be applied to real-world situations.” This means that the results of the experiment can be used to draw meaningful conclusions about the effects of the independent variable on the dependent variable.

Demonstrating Examples of Constants in Science Experiments

There are many examples of constants in science experiments. Some of the most common include the type of equipment used, the amount of time allotted for the experiment, the temperature of the environment, and the amount of light or water used. For example, if a scientist is conducting an experiment to measure the effects of light intensity on plant growth, they would need to keep the type of equipment, the amount of time allotted, the temperature, and the amount of water used constant throughout the experiment.

Other examples of constants in science experiments include the size of the sample being tested, the concentration of any solutions used, and the type of measuring device used. For example, if a scientist is conducting an experiment to measure the rate of diffusion, they would need to keep the size of the sample, the concentration of the solution, and the type of measuring device used constant throughout the experiment.

Investigating the Impact of Constants on Scientific Results

It is important to note that not controlling constants in an experiment can have serious consequences. If a scientist does not take the necessary steps to control the constants, the results of the experiment may be unreliable and invalid. Furthermore, failing to control constants can lead to false conclusions being drawn from the results. As Dr. Sorensen states, “If scientists do not properly control the constants in an experiment, they risk drawing incorrect conclusions from their results.” Therefore, it is essential for scientists to take the necessary steps to identify and control the constants in an experiment.

Comparing and Contrasting Constants and Variables in Science Experiments

Finally, it is important to understand the differences between constants and variables in a science experiment. As mentioned previously, a constant is any factor that remains unchanged throughout the duration of the experiment, while a variable is any factor that can be changed or manipulated. Variables are typically used to measure the effects of the independent variable on the dependent variable, while constants are used to maintain consistency within the experiment.

Additionally, constants are essential for ensuring the accuracy and validity of the results. By controlling the constants, scientists can reduce the number of potential sources of error and thus increase the reliability of the data. On the other hand, variables are necessary for measuring the effects of the independent variable on the dependent variable. Without variables, scientists would not be able to measure the effects of the independent variable on the dependent variable.

In conclusion, constants are an essential part of any scientific experiment. They are used to maintain consistency within the experiment and to reduce the number of potential sources of error. Additionally, using constants can help to improve the accuracy and validity of the results. Finally, it is important to understand the differences between constants and variables in a science experiment. By understanding the role of constants in a science experiment, scientists can ensure that their results are reliable and valid.

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Difference Between Constant and Control

• Categorized under Physics , Science | Difference Between Constant and Control

As scientists continue to figure out how nature works, they do so by use of experiments, with an aim of searching for cause and effect relationships. These relationships are used to explain why things happen and allow one to predict what will happen if a certain event occurs. The role of these experiments hence is to observe and measure how changes occur in relation to other things. In an experiment, the things that change are referred to as variables.  

What is a Constant?

These are values that do not change during experiments.  

For example, in an experiment where one wants to test how the growth of plants is affected by the amount of water, factors like type of soil, temperature, type of plant and sunlight all stay the same in the course of the experiment. These are hence referred to as the constants in this experiment, while the amount of water is the control.    

Other examples include freezing and boiling points of water, the speed of light,  

What is Controls?

A controlled variable is a variable that could change but is intentionally kept constant in order to clearly show the relationship between dependent and independent variables. It is also a variable that is not of primary interest and hence constitutes a third factor whose influence is to be controlled or eliminated. These variables either need to be kept constant during the experiment or be monitored and recorded. This ensures that their influence can be assessed. Most experiments have more than one control.  

An example used to explain control variable is the effect of fertilizers on a plants growth, whereby the growth of plants differs based on the amount of fertilizer used. The fertilizer, in this case, is the control variable.  

Other examples include time, pressure and temperature.

Similarities between Constant Vs. Control

• Both are important in experiments as they determine the outcome

Differences between Constant and Control

A constant variable does not change. A control variable on the other hand changes, but is intentionally kept constant throughout the experiment so as to show the relationship between dependent and independent variables.  

Primary interest

While the constant is the variable of primary interest, the control is not; hence its influence can be controlled or eliminated.  

Constant vs. Control: Comparison Table

Summary of Constant vs. Control

In an experiment, both constant and control variables are important as they influence the outcomes of the experiments.  

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The Role of a Controlled Variable in an Experiment

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A controlled variable is one which the researcher holds constant (controls) during an experiment. It is also known as a constant variable or simply as a "control." The control variable is not part of an experiment itself—it is neither the independent nor dependent variable —but it is important because it can have an effect on the results. It is not the same as a control group.

Any given experiment has numerous control variables, and it's important for a scientist to try to hold all variables constant except for the independent variable. If a control variable changes during an experiment, it may invalidate the correlation between the dependent and independent variables. When possible, control variables should be identified, measured, and recorded.

Examples of Controlled Variables

Temperature is a common type of  controlled variable . If a temperature is held constant during an experiment, it is controlled.

Other examples of controlled variables could be an amount of light, using the same type of glassware, constant humidity , or duration of an experiment.

Importance of Controlled Variables

Although control variables may not be measured (though they are often recorded), they can have a significant effect on the outcome of an experiment. Lack of awareness of control variables can lead to faulty results or what are called "confounding variables." Additionally, noting control variables makes it easier to reproduce an experiment and establish the relationship between the independent and dependent variables .

For example, say you are trying to determine whether a particular fertilizer has an effect on plant growth. The independent variable is the presence or absence of the fertilizer, while the dependent variable is the height of the plant or rate of growth. If you don't control the amount of light (e.g., you perform part of the experiment in the summer and part during the winter), you may skew your results.

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Experiment Definition in Science – What Is a Science Experiment?

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.

Experiment Definition in Science

By definition, an experiment is a procedure that tests a hypothesis. A hypothesis, in turn, is a prediction of cause and effect or the predicted outcome of changing one factor of a situation. Both the hypothesis and experiment are components of the scientific method. The steps of the scientific method are:

• Make observations.
• Ask a question or identify a problem.
• State a hypothesis.
• Perform an experiment that tests the hypothesis.
• Based on the results of the experiment, either accept or reject the hypothesis.
• Draw conclusions and report the outcome of the experiment.

Key Parts of an Experiment

The two key parts of an experiment are the independent and dependent variables. The independent variable is the one factor that you control or change in an experiment. The dependent variable is the factor that you measure that responds to the independent variable. An experiment often includes other types of variables , but at its heart, it’s all about the relationship between the independent and dependent variable.

Examples of Experiments

Fertilizer and plant size.

For example, you think a certain fertilizer helps plants grow better. You’ve watched your plants grow and they seem to do better when they have the fertilizer compared to when they don’t. But, observations are only the beginning of science. So, you state a hypothesis: Adding fertilizer increases plant size. Note, you could have stated the hypothesis in different ways. Maybe you think the fertilizer increases plant mass or fruit production, for example. However you state the hypothesis, it includes both the independent and dependent variables. In this case, the independent variable is the presence or absence of fertilizer. The dependent variable is the response to the independent variable, which is the size of the plants.

Now that you have a hypothesis, the next step is designing an experiment that tests it. Experimental design is very important because the way you conduct an experiment influences its outcome. For example, if you use too small of an amount of fertilizer you may see no effect from the treatment. Or, if you dump an entire container of fertilizer on a plant you could kill it! So, recording the steps of the experiment help you judge the outcome of the experiment and aid others who come after you and examine your work. Other factors that might influence your results might include the species of plant and duration of the treatment. Record any conditions that might affect the outcome. Ideally, you want the only difference between your two groups of plants to be whether or not they receive fertilizer. Then, measure the height of the plants and see if there is a difference between the two groups.

Salt and Cookies

You don’t need a lab for an experiment. For example, consider a baking experiment. Let’s say you like the flavor of salt in your cookies, but you’re pretty sure the batch you made using extra salt fell a bit flat. If you double the amount of salt in a recipe, will it affect their size? Here, the independent variable is the amount of salt in the recipe and the dependent variable is cookie size.

Test this hypothesis with an experiment. Bake cookies using the normal recipe (your control group ) and bake some using twice the salt (the experimental group). Make sure it’s the exact same recipe. Bake the cookies at the same temperature and for the same time. Only change the amount of salt in the recipe. Then measure the height or diameter of the cookies and decide whether to accept or reject the hypothesis.

Examples of Things That Are Not Experiments

Based on the examples of experiments, you should see what is not an experiment:

• Making observations does not constitute an experiment. Initial observations often lead to an experiment, but are not a substitute for one.
• Making a model is not an experiment.
• Neither is making a poster.
• Just trying something to see what happens is not an experiment. You need a hypothesis or prediction about the outcome.
• Changing a lot of things at once isn’t an experiment. You only have one independent and one dependent variable. However, in an experiment, you might suspect the independent variable has an effect on a separate. So, you design a new experiment to test this.

Types of Experiments

There are three main types of experiments: controlled experiments, natural experiments, and field experiments,

• Controlled experiment : A controlled experiment compares two groups of samples that differ only in independent variable. For example, a drug trial compares the effect of a group taking a placebo (control group) against those getting the drug (the treatment group). Experiments in a lab or home generally are controlled experiments
• Natural experiment : Another name for a natural experiment is a quasi-experiment. In this type of experiment, the researcher does not directly control the independent variable, plus there may be other variables at play. Here, the goal is establishing a correlation between the independent and dependent variable. For example, in the formation of new elements a scientist hypothesizes that a certain collision between particles creates a new atom. But, other outcomes may be possible. Or, perhaps only decay products are observed that indicate the element, and not the new atom itself. Many fields of science rely on natural experiments, since controlled experiments aren’t always possible.
• Field experiment : While a controlled experiments takes place in a lab or other controlled setting, a field experiment occurs in a natural setting. Some phenomena cannot be readily studied in a lab or else the setting exerts an influence that affects the results. So, a field experiment may have higher validity. However, since the setting is not controlled, it is also subject to external factors and potential contamination. For example, if you study whether a certain plumage color affects bird mate selection, a field experiment in a natural environment eliminates the stressors of an artificial environment. Yet, other factors that could be controlled in a lab may influence results. For example, nutrition and health are controlled in a lab, but not in the field.
• Bailey, R.A. (2008). Design of Comparative Experiments . Cambridge: Cambridge University Press. ISBN 9780521683579.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 0-521-29925-X.
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Holland, Paul W. (December 1986). “Statistics and Causal Inference”.  Journal of the American Statistical Association . 81 (396): 945–960. doi: 10.2307/2289064
• Stohr-Hunt, Patricia (1996). “An Analysis of Frequency of Hands-on Experience and Science Achievement”. Journal of Research in Science Teaching . 33 (1): 101–109. doi: 10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z

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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).

Table of contents

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

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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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.

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