As a result of studying the discipline, the student must be able to demonstrate the following learning outcomes:
- formation of students' in-depth ideas about methods of business process analysis;
- acquisition of students' skills in the construction of economic and mathematical models used in the business environment;
- development of methods of application of data mining for research of various processes that are inherent in business;
- formation of knowledge on adequate choice of form of economic and mathematical model taking into account the dynamics of the external environment.
- students acquire skills to formulate basic principles and prerequisites for making a business forecast.

The learning outcomes of this discipline detail the following programmatic learning outcomes:
1. the ability to reproduce and describe the basic concepts of multidimensional analysis;
2. the ability to apply multidimensional analysis methods (cluster analysis, multidimensional scaling, combinational and discriminant analysis) in public organizations;
3. the ability to isolate and analyze multidimensional objects in public administration;
4. the ability to conduct population studies using parametric and non-parametric analysis;
5. integrate and apply the acquired knowledge from different cross-curricular areas in the process of solving theoretical and applied problems in a specific field of research;
6. to choose and apply the methodology and tools of scientific research in carrying out theoretical and empirical research in the field of academic entrepreneurship;
7. to carry out scientific researches and carry out scientific projects on the basis of identification of actual scientific problems, definition of goals and tasks, formation and critical analysis of information base, substantiation and commercialization of research results, formulation of author's conclusions and proposals;
8. to carry out economic-mathematical modeling and socio-economic diagnostics of different processes and objects in the field of marketing of innovations.

Global integration processes
Public Sector Reform
Strategies for competitive development of the state

The role of data in managerial decision making. The use of descriptive statistics tools in the analysis of information Statistical hypotheses and their role in business analytics Multiple regression. Model construction under multicollinearity conditions Cluster analysis. Dynamic and spatial cluster analysis in statistical studies Discriminant analysis methods for evaluating business processes Development of a grounded information space for statistical studies using factor analysis Use of data mining techniques in public administration

1. Anderson T. Introduction to multidimensional statistical analysis / T. Anderson. - M.: Fizmatlit, 1963. - 263 p.
2. Barsegian AA Data Mining Technology, Visual Mining, Text Mining, OLAP / AA Barsegian. - Cbb. : BHC-Petersburg, 2007. - 384 p.
3. VP Borovikov A popular introduction to the STATISTICA program / VP Borovikov. - M.: Williams Publishing House, 2008. - 267 p.
4. NN Bureeva, Multivariate Statistical Analysis Using STATISTICA, PP / NN Bureeva. - Nizhny Novgorod, 2007. - 112 p.
5. Zakharchenko NI Business statistics and forecasting in MS Excel / NI Zakharchenko. - M.: Williams Publishing House, 2004. - 208 p.
6. Kuprienko NV Statistics. Methods of analysis of distributions. Selective observation / NV Kuprienko. - St. Petersburg. : Polytechnic Publishing House. Univ., 2009. - 138 p.
7. Paklin NB Business analytics: from data to knowledge / NB Paklin, VI Oreshkov. - St. Petersburg. : Ed. Peter, 2009. - 624 p.
8. Siegel F. Andrew. Practical Business Statistics / Siegel F. Andrew; trans. with English. - M.: Williams Publishing House, 2008. - 1056 p.
9. Statistics: a textbook / ed. doc. econom. of Sciences, Professor O. Rayevneva - H.: Ed. KhNEU, 2010. - 520 p.
10. Halafyan AA STATISTICA 6. Statistical analysis of data / AA Khalafyan. - M.: Binom-Press LLC, 2008. - 512 sec.

Current control - 40 points.
Examination work - 60 points.