The independent variable, also known as the manipulated variable, lies at the heart of any quantitative experimental design.
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This is the factor manipulated by the researcher, and it produces one or more results, known as dependent variables. There are often not more than one or two independent variables tested in an experiment, otherwise it is difficult to determine the influence of each upon the final results.
There may be more than several dependent variables, because manipulating the independent can influence many different things.
For example, an experiment to test the effects of a certain fertilizer, upon plant growth, could measure height, number of fruits and the average weight of the fruit produced. All of these are valid analyzable factors, arising from the manipulation of one independent variable, the amount of fertilizer.
Potential Complexities of the Independent Variable
The term independent variable is often a source of confusion; many people assume that the name means that the variable is independent of any manipulation.
The name arises because the variable is isolated from any other factor, allowing experimental manipulation to establish analyzable results.
Some research papers appear to give results manipulating more than one experimental variable, but this is usually a false impression.
Each manipulated variable is likely to be an experiment in itself, one area where the words 'experiment' and 'research' differ. It is simply more convenient for the researcher to bundle them into one paper, and discuss the overall results.
The botanical researcher above might also study the effects of temperature, or the amount of water on growth, but these must be performed as discrete experiments, with only the conclusion and discussion amalgamated at the end.
Independent Variables - Examples
As an example of an experiment with easily defined experimental variables, Mendel's famous Pea Plant Experiment is a good choice.
The Austrian monk cross-pollinated pea plants, trying to establish which characteristics were passed down through the generations. In this case, the inheritable characteristic of the parent plant was the independent variable. For example, when plants with green seedpods were crossed with plants with yellow seedpods, pod color was the independent variable.
In the Bandura Bobo Doll experiment, whether the children were exposed to an aggressive adult, or to a passive adult, was the independent variable.
This experiment is a prime example of how the concept of experimental variables can become a little complex. He also studied the differences between boys and girls, with gender as an independent variable. Surely, this is breaking the rules of only having one manipulated variable!
In fact, this is a prime example of performing multiple experiments at the same time. If you study carefully the structure of the research design, you will see that the Bobo Doll Experiment should have been called the Bobo Doll Experiments.
It was actually four experiments, each with their own hypothesis and variables, running concurrently. It would have been expensive, and possibly unethical, to test the children four times and, if the same children were used each time, their behavior may have changed with repetition.
Careful design allowed Bandura to test different hypotheses as part of the same research.