What Are the Independent and Dependent Variables That Scientists Use?
The scientific method is a means of investigating the natural world using experimentation. A hypothesis is an educated guess designed to explain something about the natural world. An experiment is a controlled investigation wherein the experimental subjects are exposed to a variety of conditions in order to determine if a particular hypothesis is true or false. Scientists analyze the subjects' responses to these conditions, and draw conclusions from them. To understand scientific experimentation, you must understand how both dependent and independent variables function in the setup of an experiment.
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Independent Variables
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The independent variable is the factor in an experiment that will remain unaltered by the experiment. It is the factor that the experimenter controls. He decides whether or not the experimental subjects are exposed to the independent variable. The experimenter might also decide how much of the independent variable to expose the subject(s) to.
Dependent Variables
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The dependent variable is the factor in an experiment that will be altered by the experiment. This is the factor that the experimenter has no direct control over. This factor depends instead on the independent variable. By observing the dependent variable, the experimenter can determine whether there is any connection between the independent and dependent variables such as a cause and effect relationship or a simple association. If the scientist's hypothesis is correct, the dependent variable will change when it is exposed to the independent variable.
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An Example
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As an example, consider an experiment designed to test the hypothesis that private tutoring results in higher graduation rates. In the experiment, some of the students at a school receive tutoring for a year before graduating. The tutoring is the independent variable. The rate of graduation is the dependent variable.
Two Groups
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In order to properly assess what, if any, connection exists between the independent and dependent variables, scientists need to separate their experimental subjects into two groups. One of these is the test group, the one exposed to the independent variable. The other is the control group, not exposed to the independent variable. If there is no difference between the test and control groups, then a connection between the independent and dependent variables is less likely.
Correlation and Causation
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Remember, correlation does not necessarily imply causation. Just because changes in the dependent variable in an experiment is associated with changes in the independent variable does not prove that the dependent variable is the effect of the independent variable. It could be that both of them are linked by a third, hidden variable. As an example, consider an experiment that seeks to discover a connection between baseball games and hot dog consumption. Even if the study shows that people who watch more baseball eat more hot dogs, it does not prove that watching baseball causes people to eat more hot dogs. It could simply be that people who tend to like baseball also tend to like hot dogs. Experiments must be carefully set up to eliminate the possibility of such hidden connections in order to prove the hypotheses they set out to test.
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