Abstract:

Statistics is one of the most used application parts of mathematics. At present, we can say that it is used in all scientific disciplines. Most of course in the natural sciences, but currently also in psychology, social sciences, medicine. It is interesting to use, for example, in literature, archeology, fine arts. This means that statistics are dealt with by a large number of professionals who are not professional statisticians, but are regular users. Therefore, we decided to write this paper, in which we described the possibilities of using the environment of the R language not only for mathematics and statistics, but especially for other professions.

There are a large number of professional tools that allow students to focus on justifying results rather than lengthy calculations. Unfortunately, all such funds are for a fee. For most students, they are either hard to reach or not available at all.

That's why we decided to support the teaching of statistics using two free tools - the R language environment and the Python environment. Both tools allow you to process non-traditional or special tasks. At the same time, the student can find many new findings through professionally created, but above all described packages - packages, which are solved using advanced statistical technology. Such an approach necessarily leads to the drawing of new knowledge through new challenges - solving problems at the limit of students' knowledge.

In this article we will mention the use of the R language environment. The text will compare the R language environment and the Wolfram platform, which is still used for teaching. A study comparing the possibilities of both applications is performed. Students have the opportunity to enroll in courses that are solved using one or the other variant. Of course, there are courses in which they learn the basics of both application environments.

Finally, we present recommendations that specify the possibilities of teaching mathematical statistics using the support of the R language. Essential properties must be revealed to students in lectures and seminars. We therefore set tasks that motivate the creation of our own environment for their solution.

Keywords:

Statistics, mathematics, language.