In scientific experiments, understanding the different types of variables is crucial for designing experiments and interpreting results. Here’s a breakdown of each term:
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Manipulated Variable (Independent Variable): This is the variable that the experimenter changes or controls in an experiment to test its effects on the responding variable. It is what you manipulate to see how it affects another variable. For example, in an experiment to determine how light exposure affects plant growth, the amount of light (e.g., hours of light per day) would be the manipulated variable.
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Responding Variable (Dependent Variable): This is the variable that is measured or observed in response to changes made to the manipulated variable. It is the outcome that is affected by the manipulated variable. Continuing with the plant growth example, the height of the plants could be the responding variable, as it is what you measure after varying the light exposure.
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Control Variable (Constant Variable): These are the variables that are kept constant or controlled throughout the experiment to ensure that any changes in the responding variable can be attributed solely to the manipulated variable. In the plant growth experiment, control variables might include soil type, water amount, plant species, and temperature.
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Controlled Variable: This term is often used interchangeably with "control variable." However, in some contexts, it may specifically refer to the group in an experiment that does not receive the experimental treatment and is used as a baseline for comparison. For instance, if you're testing the effect of a fertilizer on plant growth, a group of plants that does not receive fertilizer would serve as the controlled or control group.
In summary, the manipulated variable is what you change, the responding variable is what you measure, and the control variables are what you keep constant to ensure a fair test.