Final answer:
In a scientific experiment, manipulating the independent variable and controlling for lurking variables helps establish a cause-and-effect relationship between variables. Proper design and implementation of controls are crucial to ensure that observed changes in the dependent variable are attributed solely to the independent variable.
Step-by-step explanation:
Understanding Cause and Effect in Scientific Experiments
If there is a cause and effect relationship, the independent variable can be manipulated to observe changes in the dependent variable. In a well-designed scientific experiment, the researcher will isolate the explanatory variable by using random assignment to spread potential lurking variables evenly among groups. This ensures the observed effect on the response variable is due solely to the manipulation of the independent variable, also known as the treatment.
To definitively prove a cause-and-effect relationship, control groups must be used. The control group may receive a placebo or no treatment, to protect against bias and ensure that any observed changes are attributable to the independent variable. Other variables in the experiment should be kept constant to prevent them from affecting the dependent variable.
By manipulating the independent variable and observing the dependent variable, researchers can determine the effect of one on the other. Any experiment must also include control variables, to nullify the effect of extraneous factors that could influence the dependent variable. This robust methodology is necessary to substantiate causal inferences drawn from experimental data.