In an experiment, it's generally advisable to test one independent variable at a time to isolate its effects on the dependent variable. This approach allows for clearer conclusions about the relationship between the variables. However, if resources permit and the experiment design allows, testing a limited number of independent variables in a factorial design can provide insights into interactions without overwhelming complexity. Ultimately, the number of independent variables should balance clarity, feasibility, and the specific goals of the experiment.
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