- Science, Tech, Math ›
- Chemistry ›
The Difference Between Control Group and Experimental Group
- Chemical Laws
- Periodic Table
- Projects & Experiments
- Scientific Method
- Biochemistry
- Physical Chemistry
- Medical Chemistry
- Chemistry In Everyday Life
- Famous Chemists
- Activities for Kids
- Abbreviations & Acronyms
- Weather & Climate
- Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
- B.A., Physics and Mathematics, Hastings College
In an experiment , data from an experimental group is compared with data from a control group. These two groups should be identical in every respect except one: the difference between a control group and an experimental group is that the independent variable is changed for the experimental group, but is held constant in the control group.
Key Takeaways: Control vs. Experimental Group
- The control group and experimental group are compared against each other in an experiment. The only difference between the two groups is that the independent variable is changed in the experimental group. The independent variable is "controlled", or held constant, in the control group.
- A single experiment may include multiple experimental groups, which may all be compared against the control group.
- The purpose of having a control is to rule out other factors which may influence the results of an experiment. Not all experiments include a control group, but those that do are called "controlled experiments."
- A placebo may also be used in an experiment. A placebo isn't a substitute for a control group because subjects exposed to a placebo may experience effects from the belief they are being tested; this itself is known as the placebo effect.
What Are Is an Experimental Group in Experiment Design?
An experimental group is a test sample or the group that receives an experimental procedure. This group is exposed to changes in the independent variable being tested. The values of the independent variable and the impact on the dependent variable are recorded. An experiment may include multiple experimental groups at one time.
A control group is a group separated from the rest of the experiment such that the independent variable being tested cannot influence the results. This isolates the independent variable's effects on the experiment and can help rule out alternative explanations of the experimental results.
While all experiments have an experimental group, not all experiments require a control group. Controls are extremely useful where the experimental conditions are complex and difficult to isolate. Experiments that use control groups are called controlled experiments .
A Simple Example of a Controlled Experiment
A simple example of a controlled experiment may be used to determine whether or not plants need to be watered to live. The control group would be plants that are not watered. The experimental group would consist of plants that receive water. A clever scientist would wonder whether too much watering might kill the plants and would set up several experimental groups, each receiving a different amount of water.
Sometimes setting up a controlled experiment can be confusing. For example, a scientist may wonder whether or not a species of bacteria needs oxygen in order to live. To test this, cultures of bacteria may be left in the air, while other cultures are placed in a sealed container of nitrogen (the most common component of air) or deoxygenated air (which likely contained extra carbon dioxide). Which container is the control? Which is the experimental group?
Control Groups and Placebos
The most common type of control group is one held at ordinary conditions so it doesn't experience a changing variable. For example, If you want to explore the effect of salt on plant growth, the control group would be a set of plants not exposed to salt, while the experimental group would receive the salt treatment. If you want to test whether the duration of light exposure affects fish reproduction, the control group would be exposed to a "normal" number of hours of light, while the duration would change for the experimental group.
Experiments involving human subjects can be much more complex. If you're testing whether a drug is effective or not, for example, members of a control group may expect they will not be unaffected. To prevent skewing the results, a placebo may be used. A placebo is a substance that doesn't contain an active therapeutic agent. If a control group takes a placebo, participants don't know whether they are being treated or not, so they have the same expectations as members of the experimental group.
However, there is also the placebo effect to consider. Here, the recipient of the placebo experiences an effect or improvement because she believes there should be an effect. Another concern with a placebo is that it's not always easy to formulate one that truly free of active ingredients. For example, if a sugar pill is given as a placebo, there's a chance the sugar will affect the outcome of the experiment.
Positive and Negative Controls
Positive and negative controls are two other types of control groups:
- Positive control groups are control groups in which the conditions guarantee a positive result. Positive control groups are effective to show the experiment is functioning as planned.
- Negative control groups are control groups in which conditions produce a negative outcome. Negative control groups help identify outside influences which may be present that were not unaccounted for, such as contaminants.
- Bailey, R. A. (2008). Design of Comparative Experiments . Cambridge University Press. ISBN 978-0-521-68357-9.
- Chaplin, S. (2006). "The placebo response: an important part of treatment". Prescriber : 16–22. doi: 10.1002/psb.344
- Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
- What is the Difference Between Molarity and Molality?
- The Difference Between Intensive and Extensive Properties
- The Difference Between Homogeneous and Heterogeneous Mixtures
- Examples of Polar and Nonpolar Molecules
- How to Draw a Lewis Structure
- Ionic vs. Covalent Bonds: How Are They Different?
- How to Calculate Density of a Gas
- How to Balance Chemical Equations
- What Is Alum and How Is It Used?
- The Visible Spectrum: Wavelengths and Colors
- Examples of Physical Changes
- Chemistry Glassware Types, Names and Uses
- Fun and Interesting Chemistry Facts
- Table of Electrical Resistivity and Conductivity
- Molarity Definition in Chemistry
- Chemical Properties of Matter
Home » experimental control important
What An Experimental Control Is And Why It’s So Important
Daniel Nelson
An experimental control is used in scientific experiments to minimize the effect of variables which are not the interest of the study. The control can be an object, population, or any other variable which a scientist would like to “control.”
You may have heard of experimental control, but what is it? Why is an experimental control important? The function of an experimental control is to hold constant the variables that an experimenter isn’t interested in measuring.
This helps scientists ensure that there have been no deviations in the environment of the experiment that could end up influencing the outcome of the experiment, besides the variable they are investigating. Let’s take a closer look at what this means.
You may have ended up here to understand why a control is important in an experiment. A control is important for an experiment because it allows the experiment to minimize the changes in all other variables except the one being tested.
To start with, it is important to define some terminology.
Terminology Of A Scientific Experiment
Randomization is important as it allows for more non-biased results in experiments. Random numbers generators are often used both in scientific studies as well as on 지노 사이트 to make outcomes fairer.
Scientists use the scientific method to ask questions and come to conclusions about the nature of the world. After making an observation about some sort of phenomena they would like to investigate, a scientist asks what the cause of that phenomena could be. The scientist creates a hypothesis, a proposed explanation that answers the question they asked. A hypothesis doesn’t need to be correct, it just has to be testable.
The hypothesis is a prediction about what will happen during the experiment, and if the hypothesis is correct then the results of the experiment should align with the scientist’s prediction. If the results of the experiment do not align with the hypothesis, then a good scientist will take this data into consideration and form a new hypothesis that can better explain the phenomenon in question.
Independent and Dependent Variables
In order to form an effective hypothesis and do meaningful research, the researcher must define the experiment’s independent and dependent variables . The independent variable is the variable which the experimenter either manipulates or controls in an experiment to test the effects of this manipulation on the dependent variable. A dependent variable is a variable being measured to see if the manipulation has any effect.
Photo: frolicsomepl via Pixabay, CC0
For instance, if a researcher wanted to see how temperature impacts the behavior of a certain gas, the temperature they adjust would be the independent variable and the behavior of the gas the dependent variable.
Control Groups and Experimental Groups
There will frequently be two groups under observation in an experiment, the experimental group, and the control group . The control group is used to establish a baseline that the behavior of the experimental group can be compared to. If two groups of people were receiving an experimental treatment for a medical condition, one would be given the actual treatment (the experimental group) and one would typically be given a placebo or sugar pill (the control group).
Without an experimental control group, it is difficult to determine the effects of the independent variable on the dependent variable in an experiment. This is because there can always be outside factors that are influencing the behavior of the experimental group. The function of a control group is to act as a point of comparison, by attempting to ensure that the variable under examination (the impact of the medicine) is the thing responsible for creating the results of an experiment. The control group is holding other possible variables constant, such as the act of seeing a doctor and taking a pill, so only the medicine itself is being tested.
Why Are Experimental Controls So Important?
Experimental controls allow scientists to eliminate varying amounts of uncertainty in their experiments. Whenever a researcher does an experiment and wants to ensure that only the variable they are interested in changing is changing, they need to utilize experimental controls.
Experimental controls have been dubbed “controls” precisely because they allow researchers to control the variables they think might have an impact on the results of the study. If a researcher believes that some outside variables could influence the results of their research, they’ll use a control group to try and hold that thing constant and measure any possible influence it has on the results. It is important to note that there may be many different controls for an experiment, and the more complex a phenomenon under investigation is, the more controls it is likely to have.
Not only do controls establish a baseline that the results of an experiment can be compared to, they also allow researchers to correct for possible errors. If something goes wrong in the experiment, a scientist can check on the controls of the experiment to see if the error had to do with the controls. If so, they can correct this next time the experiment is done.
A Practical Example
Let’s take a look at a concrete example of experimental control. If an experimenter wanted to determine how different soil types impacted the germination period of seeds , they could set up four different pots. Each pot would be filled with a different soil type, planted with seeds, then watered and exposed to sunlight. Measurements would be taken regarding how long it took for the seeds to sprout in the different soil types.
Photo: Kaz via Pixabay, CC0
A control for this experiment might be to fill more pots with just the different types of soil and no seeds or to set aside some seeds in a pot with no soil. The goal is to try and determine that it isn’t something else other than the soil, like the nature of the seeds themselves, the amount of sun they were exposed to, or how much water they are given, that affected how quickly the seeds sprouted. The more variables a researcher controlled for, the surer they could be that it was the type of soil having an impact on the germination period.
Not All Experiments Are Controlled
“It doesn’t matter how beautiful your theory is, it doesn’t matter how smart you are. If it doesn’t agree with experiment, it’s wrong.” — Richard P. Feynman
While experimental controls are important , it is also important to remember that not all experiments are controlled. In the real world, there are going to be limitations on what variables a researcher can control for, and scientists often try to record as much data as they can during an experiment so they can compare factors and variables with one another to see if any variables they didn’t control for might have influenced the outcome. It’s still possible to draw useful data from experiments that don’t have controls, but it is much more difficult to draw meaningful conclusions based on uncontrolled data.
Though it is often impossible in the real world to control for every possible variable, experimental controls are an invaluable part of the scientific process and the more controls an experiment has the better off it is.
← Previous post
Next post →
IMAGES
VIDEO