Final answer:
Multiple variables in an experiment can complicate the determination of a cause and effect relationship, leading to unclear or unreliable conclusions because it is challenging to attribute observed effects to a single cause.
Step-by-step explanation:
Why should you not have multiple variables in an experiment? How will multiple variables affect the conclusion? The answer to this question is C. Multiple variables can make it difficult to determine the cause and effect relationship and can lead to an unclear or unreliable conclusion. In an experiment, it is crucial to isolate the effect of the independent variable on the dependent variable. By controlling for other potential confounding variables, researchers ensure that any change in the dependent variable is directly attributable to the manipulation of the independent variable. If an experiment includes multiple independent variables without proper control, it becomes nearly impossible to attribute the observed effect to a specific cause, leading to confounding and unreliable conclusions. The presence of a control group and randomized assignment of experimental units are strategies used to control for lurking variables and to prove a cause-and-effect connection between the explanatory and the response variables.