As a domain expert in experimental design and analysis, I understand the critical importance of conducting high-quality experiments to ensure reliable and valid results. Here are the qualities that I believe define a good experiment: 1. Clarity of Objective: The purpose of the experiment should be clear and well-defined. This objective guides the entire experimental process and helps in designing the methodology. 2. Hypothesis Formulation: A good experiment begins with a testable hypothesis. This hypothesis should be based on existing knowledge and theories and should be framed in a way that it can be either supported or refuted by the experiment. 3. Manipulation and Control: The defining characteristics of experiments are indeed manipulation and control. The independent variable, which is manipulated by the experimenter, is the key factor that the experiment is designed to test. The experimenter must ensure that this variable can be systematically altered. 4. Replicability: A good experiment should be repeatable. Other researchers should be able to replicate the experiment under the same conditions and obtain similar results. This is crucial for the credibility of the findings. 5. Control of Confounding Variables: To ensure that the results are due to the independent variable and not due to other factors, it is important to control for confounding variables. This can be achieved through randomization, matching, or statistical control. 6. Sample Size: The size of the sample should be large enough to provide statistical power. This means that the experiment should be designed to detect a meaningful effect if one exists. 7. Randomization: Random assignment of subjects to experimental conditions helps to ensure that any differences between groups are due to the independent variable and not due to other factors. 8. Blinding: In some experiments, especially in clinical trials, blinding can be a critical component. This means that neither the participants nor the researchers know which group is receiving the treatment or the control condition. 9. Ethical Considerations: The experiment should be conducted ethically, ensuring the safety and well-being of all participants. This includes obtaining informed consent and minimizing harm. 10. Data Collection and Analysis: The methods of data collection should be rigorous and systematic. The analysis should be appropriate for the type of data and the research question. 11. Documentation and Reporting: A good experiment is well-documented, with clear and detailed records of all procedures, data, and findings. The reporting of results should be transparent and include any limitations or potential biases. 12. Interpretation and Generalizability: The results should be interpreted within the context of the experiment. It is also important to consider the extent to which the findings can be generalized to other settings or populations. 13. Peer Review and Publication: The findings of the experiment should be subjected to peer review to ensure the quality and validity of the research. Publication in a reputable journal adds to the credibility of the experiment. 14. Flexibility and Adaptability: A good experimenter is flexible and ready to adapt the experimental design if preliminary results indicate that changes are necessary. 15. Transparency: All aspects of the experimental design, including any potential conflicts of interest, should be transparent to maintain the integrity of the research. Now, let's move on to the translation of the above points into Chinese. read more >>

The defining characteristics of experiments are manipulation and control. The independent variable (also known as the experimental variable) is either manipulated by the experimenter, or the experimenter takes advantage of a natural manipulation (quasi-experiment).read more >>