This study proposes a new test for testing the symmetry in the distribution of the data observed on a random variable. The test for symmetry has been constructed using a characterization result derived based on the extropy of k-records. The empirical density and critical values of the newly proposed test statistic have been obtained in this work. This study also analyses the performance of the test statistic based on the power values computed using Monte Carlo simulation methods and a comparison study with 10 competitor tests has been carried out. Moreover, the test procedure has been implemented on four real-life data sets to verify its performance in identifying the symmetric nature.

本研究提出了一种新的测试方法，用于测试在随机变量上观察到的数据分布的对称性。对称性检验是使用基于k记录的熵的表征结果构建的。在这项工作中获得了新提出的检验统计量的经验密度和临界值。本研究还根据使用蒙特卡罗模拟方法计算的功率值分析了测试统计的性能，并与 10 个竞争对手测试进行了比较研究。此外，测试程序已在四个真实数据集上实施，以验证其在识别对称性方面的性能。