The problems in teaching the methods of statistical data analysis in evidencebased medicine place high demands on their application. The rigor of the approach requires extensive knowledge in both the direct professional sphere and in areas of knowledge that go far beyond the limits of medicine. It is not enough to simply type groups for the study or calculate average values and draw some conclusions based on this. It is important to recruit groups and evaluate the statistical parameters of the obtained results correctly. Moreover, it is requisite to know the purpose of the research, formulate the appropriate hypotheses even before the beginning of the experiment [1] or data collection, and not to invent them during the analysis of an array of heterogeneous numbers and names when writing articles. The material of data processing presented at the level of schemes and algorithms in combination with the use of the appropriate programs is greatly simplified and, most importantly, streamlined. In this case, the subject of statistics is perceived not as something abstract, but as a complex component of the principles of evidencebased medicine, without detaching it from specialized training.

The involvement of specialists of the core subjects of the university sharing the examples of studies using the statistical processing and planning methods into the training will make it possible to improve orientation in a variety of the existing statistical methods of data processing, as well as to understand the importance and relevance of the use of statistics in medical research.