This article summarizes the practices of organizing research activities that can improve the training of international students in Russian universities. The authors analyzed and identified the correlation between the internal costs of research and development (R&D), the equipment in university research laboratories, and the number of foreigners studying at Russian universities. The authors used the methods of analysis and synthesis and a systematic approach to explore the experience of Russian universities in the training of international students. To identify the impact of internal R&D costs and the equipment of university research laboratories on the number of foreigners studying in Russian universities, the authors applied correlation and regression analysis, which included building a regression equation, calculating the correlation coefficient, the t-test, the coefficient of elasticity, and the coefficient of determination. This research paper revealed a strong correlation between the number of international students in the Russian Federation on the internal R&D costs and the cost of fixed assets and the equipment of Russian universities, which was proven by the calculated correlation coefficients, elasticity coefficients, and determination coefficients. The authors concluded that universities could influence the number of international students. This article proposes some methods for organizing the research activities of international students that increase their academic mobility and form the most relevant scientific and professional competencies. Higher educational institutions of any major can implement these recommendations for managing the research activities of international students. The novelty of this study lies in the fact that the authors performed the correlation and regression analysis and revealed the dependence of the number of international students in the Russian Federation on internal R&D costs, the cost of fixed assets, and the equipment of Russian universities. The authors illustrated the analysis results with the trend predictive values of factorial features and the value of the effective feature estimated according to the regression equations built. Using the calculated MAPE and Forecast Accuracy indicators for these predicted values, the authors concluded that the level of factorial features and the effective feature were predicted with high accuracy. Thus, host Russian universities can increase the number of international students through effective organization of research activities
