Final answer:
To determine causation, an experiment must be well designed with controls and random assignment. Correlation alone does not imply causation, and lurking variables must be accounted for to confidently establish a causal relationship. Significant findings in a controlled experiment suggest causation.
Step-by-step explanation:
To assess whether results provide evidence for causation of the independent variable on the dependent variable, one must consider the structure of the experimental design and the statistical significance of the findings. Correlation does not imply causation, and without proper experimental controls, like a control group and random assignment, causation cannot be confidently established. Typically, experimental research that includes randomization and control groups can suggest causation if changes in the independent variable lead to consistent and predictable changes in the dependent variable.
For instance, the dependent variable is the outcome of interest that is expected to change when the independent variable is manipulated. If an experiment investigates the impact of teaching methods (independent variable) on student learning outcomes (dependent variable) and uses random assignment and a control group, one could analyze the results for significant differences attributable to the teaching method to suggest causation. However, potential lurking variables must be considered, as they can confound results. Therefore, a well-controlled experiment with significant results increases the likelihood of establishing a causal relationship.