Define the Variables

There should be three categories of variables in every experiment: dependent, independent, and variables held constant or controlled.

Independent -- is what is purposely varied during the experiment; it is what the investigator changes to see if it has an effect on the dependent variable; the variable you change on purpose; also called manipulated variable (and in medical research can be called the treatment variable).

Example: an investigator wants to study coffee bean growth.  Possible independent variables include: amount of fertilizer, type of fertilizer, temperature, amount of H₂O, day length, type of light; all of these may affect the number of beans, weight of the plant, or height of the stem and they are things the scientist can manipulate.

Dependent -- is what will be measured; the variable that responds to a change in the independent variable; also called the responding variable (or in medicine, the outcome variable).

In our coffee bean example, possible dependent variables could be: number of beans, weight of the plant, or height of stem.

Key: Since you need to know which factor is affecting the dependent variable(s), there will probably be only ONE independent variable in your experiment. The investigator must choose the one that he/she thinks is most important. But the scientist can measure as many dependent variables as he/she thinks are important indicators of "coffee bean growth".

Constant or controlled variables:  -- the variables held constant. Since the investigator wants to study the effect of one particular independent variable, the possibility that other factors are affecting the outcome must be eliminated.  This is done by making sure factors or conditions are all the same for every trial.

For example, the above scientist must use the same type of fertilizer, or amount of H₂O, temperature, or amount of light to which the beans are exposed.

Control Group:  In some experiments, a trial is run where no change or manipulation is done.  This allows the scientist to measure what would occur without the effect of the independent variable.

For example, the bean growth experiment would allow one set of plants to grow only under the conditions he had remain 'constant' .