Methods of Multidimensional Analysis in Public Management and Administration

Major: Public Administration
Code of subject: 8.281.00.O.010
Credits: 3.00
Department: Administrative and Financial Management
Lecturer: Podolchak N. Y.
Semester: 3 семестр
Mode of study: денна
Learning outcomes: 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 by students of skills of construction of economic and mathematical models which are used in the business environment; - mastering the methods of application of data mining for the study of various processes that are inherent in entrepreneurship; - formation of knowledge on the adequate choice of the form of economic-mathematical model taking into account the dynamics of the external environment. - acquisition by students of skills of formation of the basic principles and preconditions of realization of the business forecast.
Required prior and related subjects: Previous subjects: Analytical and numerical research methods. Related and the following disciplines: Global integration processes; Marketing research and modeling in public administration.
Summary of the subject: The role of data in management decisions. Application of descriptive statistics tools in information analysis Statistical hypotheses and their role in business analytics Multiple regression. Construction of the model in the conditions of multicollinearity Cluster analysis. Dynamic and spatial cluster analysis in statistical studies Methods of discriminant analysis for assessing business processes Development of a sound information space for statistical research using factor analysis Use of data mining methods in public administration
Assessment methods and criteria: Current control - 40 points. Examination work - 60 points.
Recommended books: 1. Anderson T. Introduction to multidimensional statistical analysis / T. Anderson. - M .: Fizmatlit, 1963. - 263 p. 2. Barsegyan AA Data technology Data Mining, Visual Mining, Text Mining, OLAP / AA Barsegyan. - СПб .: БХВ-Петербург, 2007. - 384 с. 3. Moskalenko, VV Models and methods of intellectual analysis of multidimensional data under conditions of a priori uncertainty [Text]: monograph / V.V. Москаленко. - Sumy: Sumy State University, 2020. - 184 p. 4. Bureeva NN Multidimensional statistical analysis using PPP "STATISTICA" / NN Bureeva. - Nizhny Novgorod, 2007. - 112 p. 5. Zakharchenko NI Business statistics and forecasting in MS Excel / NI Zakharchenko. - М .: Издательский дом "Вильямс", 2004. - 208 с. 6. Kuprienko NV Statistics. Methods of distribution analysis. Selective observation / NV Kuprienko. - СПб. : Polytechnic Publishing House University, 2009. - 138 p. 7. Paklin NB Business analytics: from data to knowledge / NB Paklin, VI Oreshkov. - СПб. : Изд. "Peter", 2009. - 624 p. 8. Siegel F. Andrew. Practical business statistics / Siegel F. Andrew; lane. with English - М.: Издательский дом "Вильямс", 2008. - 1056 с. 9. Statistics: a textbook / ed. Dr. econ. Sciences, Professor OV Raevneva - Kh .: Ed. KhNEU, 2010. - 520 p. 10. Khalafyan AA STATISTICA 6. Statistical data analysis / AA Khalafyan. - М .: ООО "Бином-Пресс", 2008г. - 512 p. 11. Fyliuk H., Honchar I., Kolosha V. (2019). The Interrelation between Economic Growth and National Economic Competitiveness: The Case of Ukraine. Journal of Competitiveness. No. 3. pp. 53–69. 12. Erina AM International ratings: statistical aspects of calculation and application. Statistics of Ukraine. 2016. № 4. S. 56–64. 13. Gonchar I., Yashchenko J. Multidimensional statistical assessment of the impact of the birth process on the formation of the country's demographic potential. Economic analysis. 2019. T. 29. № 1. S. 13–20. 14. Gonchar IA, Korotych EG Multidimensional assessment of the attractiveness of the world: a statistical aspect. Logos. 2019. Vip. 15. S. 17–20.