Identifying Units and Trends in a Chart
When you are evaluating a research summary, you should take special care to identify the experimental control, which is the standards against which the results of the experiment are measured.
In other words, it’s the measure of what happens when the independent variable is not manipulated. In an experiment, you have an independent and a dependent variable.
This is a cause and effect relationship, you manipulate the independent variable and then you observe what happens to the dependent variable, because of what you did to the independent variable. What happens with the control is, you’re not changing the independent variable at all, because if you conducted an experiment without a control, you would not be able to determine anything from the experiment. You would be able to see what happened as a result of what you did, but you wouldn’t have anything to compare it to, so the control is there to give you something to compare it to.
An example is a scientist who wants to determine what would happen to a mouse who is fed a special diet. The control here would be the mouse receiving a normal diet. Here the independent variable is going to be the diet and the dependent variable is going to be whatever happens to the mouse, probably behavior looks or appearance.
You’re playing around with the independent variable of the diet and so say you give it a strange diet and then the mouse acts a certain way, you don’t know if that’s normal or abnormal. That’s why you have a control, which is the mouse receiving a normal diet, so you can compare the mouse receiving special diet to the mouse receiving a normal diet.
In order for the results of an experiment to be meaningful, there must be a clear and reasonable experimental control, that’s why it’s so important, like in this experiment, to have a mouse receiving a normal diet.