Scientific experiments are a core part of learning new information, supporting hypotheses, and understanding the effectiveness of current methodologies as you find new techniques to use. Variables and control groups are essential here as they help scientists draw valid conclusions that, in turn, help in finding the accuracy of results. This article discusses control groups, how different experiments require different groups, and the importance of having such groups.
Control Group – In a Nutshell
A control group is a second cohort in an experiment that is not exposed to treatment and is used to check if the change in the experimental group really stems from the treatment.
Definition: Control Group
A control group is a group of factors that are not subject to change during an experiment. In a scientific experiment, an independent variable remains constant in the control group and changes in the treatment or experimental group. These groups help establish a cause-and-effect relationship between the dependent and the independent variable.
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Experimental setting
There are different definitions and uses of the word “control group” and of it itself. The most common one is the control group that faces the experimental group in research. However, there are also the terms “positive” and “negative control group”, which are also used in science.
Experimental and Control group
Control groups are crucial for any experimental design to work. In an experiment to find new treatments, researchers usually divide the participants into at least two groups.
- Treatment or Experimental Group: The participants who received the medication that’s being tested
- Control Group: The participants have received a placebo, standard treatment with already known effects, or no treatment at all.
While conducting the research, the treatment consists of a variable manipulated by the researcher. Usually, they depend on the research performed, like in medical experiments it might be a therapy or medication, while a public policy study may focus on a new social policy. During the experiment or study, it is important to keep all variables constant between the two groups, except for the ones you are investigating. This way, you can easily measure the extent of the treatment without interference from any confounding variable.
Example
The Jane Doe cosmetics company has recently developed a long-lasting lip color product and wants to test it before its release. Testing the product first enables them to make improvements and substantiate their claims. They get study participants with the same lip color preferences and divide them into control and experimental groups.
The company assigns the experimental group the new product to use for a set time and asks them to record how long it takes for results to be visible. They also ask the control group to record how long the lip color lasts. The ones in the controlled group get a similar lip color, but they’re not using a product from the same formula.
From these records, the company can make the necessary changes.
Positive and negative Control group
A less common use of control groups is in scientific research when it is substances you are investigating instead of people. Here, the positive control group represents a substance you already know the characteristics of. This one serves as a test about whether your method works, and at the same time presents a template of what you expect from the negative one. Then you conduct the experiment with the negative control group to check your assumptions about it.
Example
An example for this could be flame coloration in chemistry. First you have a substance of which you know that it contains lithium, and it colors the flame red. Next you have your negative control group, a substance you suspect also has lithium in it. Then you hold it into the flame and see if it also turns red.
Non-experimental research
Non-experimental research is often applied when it would be too difficult to create an experiment around a topic because you have to rely on external factors or long-term experiences. There are two types of control group experiments that fall into this category.
Quasi-experimental design
In a quasi-experimental setting, the experimental and control groups are typically pre-existing already. One group of people received a certain treatment while another one did not, independently.
Example
For example, one city may have a “no car” policy in the city center, while another one does not. If you want to study the effects of having car-free areas, the first city is your experimental group, while the second one is the control group.
Matching design
In matching design studies, you match every individual of your treatment group with another person that has identical prepositions except for the variable of your research. This refers to a person of the same age, social status, diet, gender, etc. These matched people are now the control group in your experiment.
Example
An example for matching control groups might be if you investigate the connection between mental stability and owning a dog. Therefore, you sample different dog owners as your experimental group and then look for matching people that do not own a dog. In this case, the prepositions might be age, job and average stress level, as those are the ones that you want to investigate.
Importance of control groups
Control groups are important tools to ensure validity in your studies. In every research, you need to prove your point with relatable facts. When you see stats change in your experimental group, the control group is used to eliminate other possible reasons for the change.
Therefore, it is also important that the control groups are sampled correctly because invalid ones can drastically influence the results of your study, for example through confounding variables that have not been taken into consideration.
To avoid invalid control groups, make sure to sample them randomly, at best in a double-blinded manner, and keep the differences between the experimental group and the one used to control them as little as possible.
FAQs
No, the control group does not receive any treatment. It exists only to see if their equivalent of the variable is changing along with the experimental group, even without treatment to eliminate the possibilities of external factors.
Negative control groups exist especially in scientific research and are often a substance whose ingredients the researcher does not know. The positive control group is a substance they know the composition of and serves as a template.
Experimental design is planning a set of processes to study a relationship between variables.
The experimental group is the cohort of people that receives the treatment that is researched in the study.
