Types of Variables > Control Variable
An experiment has several types of variables, including a control variable (sometimes called a controlled variable). Variables are just values that can change; a good experiment only has two changing variables: the independent variable and dependent variable. Let’s say you are testing to see how the amount of light received affects plant growth:
- The independent variable, in this case the amount of light, is changed by you, the researcher.
- As you change the independent variable, you watch what happens to the dependent variable. In this case you see how much the plants grow.
- A control variable is another factor in an experiment; it must be held constant. In the plant growth experiment, this may be factors like water and fertilizer levels.
The Control Variable and Experimental Design
If control variables aren’t kept constant, they could ruin your experiment. For example, you may conclude that plants grow optimally at 4 hours of light a day. However, if your plants are receiving different fertilizer levels, your experiment becomes invalid. As a researcher, you should identify any variables that may affect the outcome of your experiment and you must take steps to keep them constant (“control” them). If you do not, your experiment compromises internal validity, which is just another way of saying your experimental results will not be valid. When control variables run amok and aren’t controlled, they turn into confounding variables, which affect your results and ruin your experiment.
Control Variables vs. Control Groups
In any experiment or research, it can be virtually impossible to account for all variables that may affect the outcome of your experiment. If it’s difficult to identify and control all potential confounding variables, it may be necessary to make a control group. A control group provides a baseline measurement for your experiment.