This paper presents a comprehensive analysis of socio-economic and demographic variables across four clusters formed on the basis of the Federal and Military Districts of the Russian Federation. The x-x-objective is to identify regional disparities and economic imbalances through multivariate assessment and statistical testing. The paper begins with an overview of Russia’s Federal and Military Districts, followed by the calculation of descriptive statistics for each cluster. Socio-economic data were obtained from authoritative sources such as ROSSTAT and EMISS, covering the period from 2010 to 2021. With these data, both MANOVA and GPA (generalized profile analysis) can be applied to our analysis to compare clusters. Moreover, MANOVA and GPA require the assumptions of multivariate normality and homogeneity of covariance matrices. To account for violations of multivariate normality and homogeneity of covariance matrices assumptions, we propose bootstrap methods of MANOVA and GPA. This approach ensured a more robust and reliable examination of significant cluster differences.

Keywords: Bootstrap, MANOVA, Generalized Profile Analysis, socio-economic factors.