1. Explain the quality of the data source: If your data source has high quality assurance, you can provide relevant certificates or documents to explain and point out the reliable reasons.
2. Discuss the repeatability of the experiment: If you have conducted many experiments and obtained similar data, you can explain the repeatability of the experiment and the possible external interference variables during the experiment.
In addition, explain the distribution of data: even if the data has no error line, distribution analysis can be used to explain the accuracy and reliability. Some commonly used data distribution analysis methods include normal distribution and skewed distribution.