Teaching statistics to future programmers using real data sets and R programming language

Abstract

This paper addresses the problem of teaching statistics to future programmers. It argues that the theoretical content of teaching statistics needs to be updated and oriented towards the practical field, even at the higher education level. It suggests that the teaching of statistics to students should move from theoretical methods to practical solutions of applied problems and emphasize the analysis and interpretation of results rather than the statistical calculations. The paper proposes a system of tasks based on real data sets obtained from statistical research as a way of improving the learning of statistics for future programmers. It shows that such tasks can increase the students’ motivation compared to synthetic examples, which are commonly used in statistics courses. The paper also reviews the software tools for statistical data analysis and identifies their features and advantages for the learning process. It recommends using R, a specialized programming language, as the main tool for teaching statistics.