CLUSTER ANALYSIS IN ESTIMATION OF LEVEL AND QUALITY OF LIFE OF POPULATION IN SUBJECTS OF THE RUSSIAN FEDERATION
The application of hierarchical cluster analysis of RF subjects from the perspective of the level and quality of life of the population is considered. On the basis of statistical information, the work presents the results of regions division according to the main indicators of the level and quality of life. The study identifies five clusters: low, below average, medium, above average and high quality of life. To characterize the subjects of the Russian Federation, a system of socio-economic indicators of the level and quality of life is used (average per capita income of the population, poverty level, life expectancy, registered unemployment, morbidity, pollution, residential area per capita, etc.).
Keywords: level and quality of life, classification of subjects, linear transformation, multivariate statistical analysis, hierarchical cluster analysis.
Highlights:
• indicators that characterize the level and quality of life of the population in the regions of the Russian Federation are identified;
• clustering of RF regions by the level and quality of life of the population is carried out;
• the analysis of the composition of clusters is carried out.
Roza V. Ovsyannikova, a Master’s Degree student, Samara State University of Economics.