The control in an experiment is the sample or component that remains the same throughout the experiment. While other factors may act on other samples, this one remains the same.
There are a number of variables in an experiment, and there is no way to interpret the data accurately without a baseline to compare it to. This is why the control is important. When testing out a process or seeing how a substance reacts, it is important to collect data from a sample that did not undergo the process or come in contact with the substance for which to make a comparison. Scientists can then quantitatively collect the results of the experiment.
Creating a Control Group
When preparing a control group, it is important that all aspects of the group are identical to the experimental group except for one factor. If there are too many inconsistencies between the two groups, then there is no way to know if the process or substance being tested is the cause of the results. For example, when testing if seeds need water to grow, all of the beans need to be in the same conditions. The subjects in the control group are the ones that do not receive water. This is the only condition that should differ. Testers are then able to note the differences between the two groups. If the control group was also lacking soil or was placed out of a path of sunlight in addition to not receiving water, then there is no way to know if the results were due to the water, soil or sunlight without testing again. Carefully preparing the control and experimental groups gives experimenters higher confidence in the accuracy of the results.
Dependent and Independent Variables
Dependent and independent variables are two other important factors in the scientific method. They are in essence the cause and effect of an experiment. They are also what separates the control group from the experimental group. The independent variable is the part of the experiment that changes. It is what the experimenter chooses to change and is not dependent on any other part of the experiment. In contrast, the dependent variable is entirely dependent on the independent variable. If the independent variable changes, then its effects are seen in the dependent variable. In the example of testing if a seed needs water to grow, the seed would be the dependent variable and the water would be the independent variable.
Importance of Controlled Experiments
The biggest advantage of controlled experiments is that they allow scientists to verify their results to a degree of certainty. By controlling all of the variables aside from one, scientists can get a more accurate picture of the results. It also makes it easier for others to replicate the results. Not all experiments have a control, though. In some instances, it is impossible to control all of the variables aside from one. Uncontrolled experiments still provide useful information, but it is harder to interpret that data with the same degree of certainty. This is especially true in the field of human testing when there will always be several variables that differ between the test subjects.