Multidimensional Data Analysis of Social and Economic Development in Russian Federation Regions
УДК 519.6:004.622
Abstract
In this paper, we examine the social and economic development level of the Russian Federation regions in 2021 using data from the Federal State Statistics Service. We employ multidimensional data analysis techniques to reduce the non-orthogonal variables via factor analysis to a small, orthogonal factor space, determine the optimal number of clusters via tree classification, and perform cluster analysis in the factor space. We calculate the position of the regions in the factor space, determine the location, composition, and statistical characteristics of clusters, and compute the volumes and densities of clusters. We identify the densest clusters, including those with close proximity and regions with significant variations from the average level of social and economic development. The study utilizes machine and graphical methods of computational mathematics and has both theoretical and practical implications.
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Copyright (c) 2023 Алексей Юрьевич Юдинцев , Галина Николаевна Трошкина
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