As part of the implementation of the university’s research activities Scientific and Practical School (SPS) as an independent structure within the work of Department of Science and Commercialization was created.
SPS is engaged in the implementation of additional curricula in the field of mathematics and economics, the development and use of modern educational technologies and forms of education, leading scientific research in the field of “Mathematical and instrumental methods of analysis and forecasting of socio-economic processes. NPS "Analytic" offers a series of analytical courses on the topic "Mathematical and statistical methods for analyzing and forecasting socio-economic processes.
"The scientific and practical school "Analytic" offers a series of analytical courses on the topic "Mathematical and statistical methods of analysis and forecasting of socio-economic processes" for students on a fee basis (price is negotiable):
1. Presentation and analysis of data
2. Econometric analysis and forecasting methods
3. Dynamic forecasting models
4. Multidimensional statistical methods
The goal of each course is to develop analytical thinking, summarize and make decisions. Each course is held in the amount of two credits and is designed for 3 months. The method of teaching courses is based on a project-based approach to the study of topics in order to increase the autonomy and analytical competence of the listener. Obligatory requirements of the courses is to perform final work on real data and after successful protection a certificate is issued. For the development of curricula in the amount of 6 credits and the preparation of a scientific project (publishing an article, making a presentation at national and international conferences), a certificate of professional development in this area of science is issued. SPS funds the participation of bachelor students who have achieved good scientific results in republican and international conferences.
The program of courses is attached.
SPS Supervisor,
Doctor of Economics, Professor R.U. Rakhmetova
Course program *
1. Presentation and analysis of data (2 credits - 90 hours)
|
№ |
Topics |
Amount of hours |
Expected results * |
|
1 |
Formulation of tasks and analysis |
4 |
Formulate the purpose of the analysis. Identify indicators and collect real data |
|
2 |
Tabular method |
6 |
Tabular views of data. |
|
3 |
Graphic method |
6 |
Graphic representation of data |
|
4 |
Mathematical and statistical methods of analysis |
6 |
Business Data Analysis |
|
|
Graduation work |
8 |
Presentation. Defense of work |
|
|
TOTAL |
30 |
|
2. Econometric methods of analysis and forecasting (2 credits-90 hours.)
|
№ |
Topics |
Amount of hours |
Expected results * |
|
1 |
Causal relationships |
10 |
Formulate the task setting. Identify causal factors and collect real data |
|
2 |
Econometric methods |
8 |
Step by step econometric studies |
|
3 |
Graduation work |
12 |
Work defense |
|
|
TOTAL |
30 |
|
3. Dynamic forecasting models (2 credits-90 hours)
|
№ |
Topics |
Amount of hours |
Expected results * |
|
1 |
Analysis of changes in time series levels |
6 |
Statistically characterize and identify the structure of the series |
|
2 |
Dynamic models |
12 |
Modeling time series trend prediction |
|
3 |
Graduation work |
12 |
Work defense |
|
|
TOTAL |
30 |
|
4. Multidimensional statistical methods (2 credits-90 hours)
|
№ |
Topics |
Amount of hours |
Expected results * |
|
1 |
Statement of the problem of multidimensional analysis |
4 |
Formulate the purpose of the analysis. Identify the object of study and collect real data |
|
2 |
Cluster analysis |
8 |
Compare and analyze classes for decision making |
|
3 |
Discriminant analysis |
8 |
Identify the competitiveness of objects |
|
4 |
Graduation work |
10 |
Work defense |
* Themes of the course program can be adjusted according to the audience's request.