E-learning has dramatically expanded the possibilities of traditional approaches and methods of teaching. Electronic educational environments have a wide range of functionality that allows to effectively organize educational material, provide students with theoretical material and assignments for practical and independent work, conduct testing and collect statistics on student academic performance. Based on the data stored in the electronic educational environment, it is possible to analyze various aspects related to the learning process. In this paper, an approach to assessing the association between categorical variables reflecting certain aspects of e-learning based on the chi-square test is discussed. Namely, it shows how to determine whether there is a statistically significant association between the indicator of students’ activity in online classes and their grades for practical and independent work. Based on this analysis, it is possible to optimize the e-learning course in order to improve student performance. #CSOC1120