The Kendall coefficient consistency test can help us evaluate the degree of consistency of evaluators or testers when evaluating the same sample. Through these results, we can understand the consistency of each indicator and make corresponding data analysis and explanations based on it. Please note that the p-value can help us determine whether consistency is significant, while Kendall's The closer the W coefficient is to 1, the higher the consistency.

    Data description:

    Background description:

    Kendall coefficient consistency test is a statistical method used to evaluate the degree of consistency of evaluators or testers when evaluating the same sample. This method is based on the Kendall rank correlation coefficient, which measures the consistency between different evaluators. Kendall's The W coefficient is between -1 and 1, and the closer it is to 1, the higher the consistency. In this analysis, we calculated the Kendall's W coefficient for different indicators and obtained corresponding statistical indicators (such as rank mean, median, Kendall's W coefficient, X) ² Value and p-value). Among them, the p-value is used to measure whether the Kendall's W coefficient is significant. When the p-value is less than 0.05, we usually consider consistency to be significant and can reject the original assumption that consistency is 0.

    The analysis results are as follows:

    The Kendall's W coefficient of the overall data is 0.022, with a p-value of 0.972, indicating that the consistency level of the overall data is not significant and the original assumption of consistency of 0 cannot be rejected.

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