СТОХАСТИЧНА ПІДГОТОВКА МАЙБУТНІХ ЕКОНОМІСТІВ У НАВЧАЛЬНИХ ЗАКЛАДАХ НІМЕЧЧИНИ
Stochastic training of future economists in the educational establishments in Germany
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This paper analyzes approaches to stochastic training of future economists in the Federal Republic of Germany. The content of stochastic training in the elementary school is revealed through a combination of content (data, frequency and probability) and general (information representation; reasoning; problem solving; modeling; automation) competencies. In the secondary school learning stochastics content is formed as a result of the interaction of content (data and identifying chances), procedural mathematical (ability to mathematical reasoning; solving mathematical problems; mathematical modeling; the use of mathematical concepts; the use of symbolic, formal and technical elements of mathematics; the ability to use mathematics in communication) and total (reproduction; depending on the installation; synthesis and reflection) competencies. The course content of stochastics in training future economists in higher education in Germany is presented as an example of modules Statistics I (Descriptive statistics and probability theory) and Statistics II (Generalizing statistics). Analysis of programs on stochastic training of future economists in Germany showed that in addition to the usual Ukrainian higher educational establishments’ topics covered throughout the course «Probability Theory and Mathematical Statistics», considerable attention is paid to the study of the theory of indexed data, regression, and time series analysis. It is also highlighted the fact that a large amount of instructional time allotted for practical stochastic training both in school and in higher education institutions. Educational material is given at a high level of visualization, designed to illustrate the theoretical material, to facilitate its perception, to identify the submission of experimental data and so on. Considerable attention is paid to the use of computer software packages that can be used during the analysis of stochastic processes and phenomena. In our opinion, this methodological approach contributes to a higher level of formation of competences aimed at the ability to deal with the significant influence of the random factors effectively and professionally. Therefore, native scientists need to pay attention to the achievements of the approaches that will be aimed at strengthening the practical component of the stochastic training of future economists.
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