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A control group is a designated group that's isolated from an experiment involving another group. This control group enables experimenters of all types to gauge the effectiveness of the experiment by comparing the results seen by the experimental group with the control group.
Typically, members of a control group are randomized, but they also tend to be similar to the members of the experimental group. For example, a control group in a marketing experiment would comprise the same type of audience as the experimental group. This would help effectively measure the results of the experiment by highlighting the differences between members of both groups.
Comparative experiments must have a control group. Without a control group, the results of an experiment will likely be inconclusive as there's no way to effectively determine whether the experiment resulted in a change to the experimental group.
Even if a change does occur among the members of the experimental group, it may be impossible to determine whether it resulted from the experiment or another factor.
While experimenters may focus primarily on the experimental group, the control group ultimately plays a vital role in measuring the results. You can go back to the control group and figure out whether the experiment was truly effective or if another variable influenced a certain outcome.
In any type of comparative experiment, you will have one or more control groups and experimental groups. The main difference between these two is that the experimental group is subject to the experiment while the control group either takes a placebo or otherwise resumes normal activities.
Other than this key difference, both groups should be virtually identical. They should consist of the same types of people, including those with similar demographics, geographic locations, and other elements. This allows for a real comparison between groups to measure the success of the experiment.
There are several types of control groups that an experiment may use, depending on the specific type of experiment and industry. Some of these control group types include the following:
In a positive control group, members receive either treatments or items that are already known to produce certain results. For instance, marketers may subject a control group to marketing materials they're already familiar with and with the same frequency. Meanwhile, the experimental group would be exposed to new materials and a change in frequency of exposure.
Negative control groups, unlike their positive counterparts, won't receive any treatment or sample during the experiment. These are often involved in studies for products such as new medications. The experimental group would receive the medication while the control group doesn't receive any treatment, enabling researchers to gauge the effects of the medication on the experimental group.
Where the negative control group doesn't receive any treatment or sample, the placebo control group will receive a placebo. This placebo is a substitute for the item the experimental group receives, such as a sugar pill replacing medication. The goal is to give the control group the illusion that it has received the medication. In these cases, researchers would allow for the influence of the placebo effect, which may produce results that are similar to the actual experiment.
A double-blind control group will play into a double-blind study, in which case the participants and the researchers are unaware of which group is the experimental or control group. Eliminating this awareness helps remove any biases from the experiment, as neither the participants nor researchers have any preconceived notions regarding the expected outcome of the experiment.
Using randomized control groups, researchers make control influences more unpredictable. This helps ensure that specific demographics and other elements don't directly cause a change.
Depending on the experiment, researchers may put together multiple control groups, which enables them to collect more data during the experiment and increase overall accuracy. In experiments with two or more control groups, members of these groups may receive a placebo or never receive one, or some may receive a placebo while others receive the treatment or nothing at all.
Some experiments may also use data collected from previous control groups in other experiments rather than create a new one. These control groups may consist of members who are similar to the members of the experimental group in the new experiment. In turn, researchers can compare the data collected in the experiment to the previous control groups without the need to put together new groups and without compromising the integrity of data.
A waitlist control group comprises participants in an experiment who will eventually participate in the experiment at some point throughout. Researchers may opt for waitlist control groups if they want to experiment over a certain period and involve multiple groups over time. They can then compare the results across these different groups and get a better idea of the effectiveness of the experimental treatment or sample as the experiment progresses.
Many types of experiments use control groups to help measure the effectiveness of new products, services, and more. Here are some examples of control groups in various types of experiments based on the applications that use them:
Many business research applications rely on experiments and control groups to determine the effectiveness of everything from marketing to new business processes. Control groups in business research may play a part in:
Many pharmaceutical companies build control groups when experimenting with new medications and other treatments. Often, these experiments involve a placebo control group that receives a substitute for the actual treatment. They may want to test a wide range of treatments, including:
Companies in the cosmetics industry also frequently experiment with new products using control and experimental groups to gauge their effectiveness. Like pharmaceutical experiments, cosmetics experiments frequently involve placebo control groups who take a placebo in place of the cosmetic product. Common experimental products in this industry include:
These are simply some of the many applications for control groups in experiments. Generally, control groups are critical for measuring the results of experiments of all types. Without a control group in place, it may be difficult or even impossible to measure the results of the experiment, leading to inconclusive results.
In the majority of cases, experiments use a minimum of one control group that either doesn't receive the experimental sample or treatment or receives a placebo. All controlled experiments use this model to compare the effects of the treatment on the experimental group with the other groups involved.
However, there are some exceptions to this model, depending on the type of experiment that researchers are conducting. These cases typically involve a within-subjects design that takes a look at how a treatment affects a single group by comparing them before and after exposure to a specific treatment.
Generally, it's ideal to have at least one control group in an experiment to determine whether the subject of the experiment causes a change or if another variable is the cause. Having control and experimental groups enables you to compare results and effectively figure out what's influencing a change in behavior and psychology, physical characteristics, and more.