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Independent Variables
An independent variable is the item that a scientist alters when conducting an experiment. For example, if you wanted to measure whether your dog behaved better when fed a different dog food, the new dog food would be the independent variable. It is important that a scientific experiment only have one independent variable. Otherwise, several factors might be causing the change noticed by the scientist. If you changed your dog's food, altered her exercise routine and praised her more frequently, you would be unable to tell which variable caused a change in behavior.
Dependent Variable
The dependent variable is named because it is affected by the independent variable. A dependent variable is the thing being measured in an experiment. In the dog food behavior example, your dog's behavior is the dependent variable. "Biology: Life on Earth with Physiology" explains that the most effective experiments define dependent variables very carefully. For example, it would be more effective to itemize specific behavioral changes you are looking for before embarking on the experiment with your dog. Looking for generalized changes in behavior might lead to misleading results.
Repeatability
Clearly-defined dependent and independent variables make experiments repeatable. When an experiment can be repeated by another scientist, it's easier to prove a hypothesis because the experiment is not dependent on the opinions of one particular observer. For the dog training experiment, a highly repeatable experiment would be one in which the specific brand and amount of dog food was clearly listed and the specific behavior changes, as well as the speed and frequency of the changes, were explained.
Hidden Variables
Although science experiments attempt to control all variables, there are frequently hidden variables that alter the outcome of an experiment. For example, if the weather changes while you are conducting your dog food behavior experiment, this could affect your dog's behavior. Philosopher of science W.V.O. Quine argued that it is impossible to control all variables. He explained that, if a scientist witnessed a change under a microscope as a result of a chemical reaction, the cause might not be the chemical reaction. The cause could easily be the brand of microscope, the weather, the quality of the experimenter's vision and a host of other factors. The best science experiments address hidden variables that were not tested but were difficult to control.