Final answer:
Scientists conduct statistical analysis to determine if observed differences between experimental and control groups are statistically significant and not due to chance. This is a key method in the realm of experimental design to assure that the outcomes are a result of the physiological differences caused by the experimental treatment.
Step-by-step explanation:
To ensure that differences in experimental and control groups are due to physiological differences rather than random chance, scientists utilize a process of statistical analysis. This analysis assesses if the outcomes are statistically significant, meaning that the likelihood of the observed results being due to chance is very low. In experimental design, random assignment is crucial to control for lurking variables, and the only intended difference between the experimental group and the control group should be exposure to the independent variable or experimental manipulation. When such rigorous methods are used, researchers can be more confident in attributing differences in outcomes to the intervention being tested, rather than to confounding variables or chance.
Interpreting experimental findings requires this statistical analysis to set a threshold for significance, often at a p-value of less than 0.05, to reduce the risk of false positive results. Importantly, ethical considerations must also guide experimental design, notably when the manipulation of variables could cause harm to the participants.