Statistical relationships between indicators of favourable living environments in biosphere compatible cities

Abstract Introduction. National goals and strategic objectives of the Russian Federation encompass the development of comfortable and safe urban environments. Pursuant to the goals and objectives, set by the state, the comfort of urban environments must be improved and the value of its quality index must go up, while the number of cities having unfavorable living environments must go down in the short term. Environmental deterioration, which is underway in many cities, sets the task of developing new urban living principles that regulate the biosphere compatibility of cities and the development of human capital. Materials and methods. The theoretical basis of this research project is the paradigm of life activities — biosphere-compatible cities and settlements capable of developing humans, as well as its fundamental provisions concerning the assessment of social standing, the pace of human development, and the application of social standards to public relations. Practical tools, that may be used to solve this problem, include the correlation and regression analysis that serves to identify the statistical relationships between dependent/independent variables of interacting factors and social and demographic indicators of residential areas (micro-districts/blocks) in municipalities. Results. The co-authors propose a new system of indicators, that will be used to assess the condition of the living environment. It expands the traditional notions of urban planning and quality of life in urbanized territories following the principle of urban functions employed to satisfy rational human needs. Statistical data on the availability of urban functions in 17 residential districts of the 15 cities of the Russian Federation was analyzed to choose the type of the regression model and perform the numerical evaluation of its parameters. The results of the correlation and regression analysis of dependent and independent variables, performed in this paper, substantiate the choice of the most significant interacting factors and their rightful contribution to statistical models used to forecast most favorable living conditions. Conclusions. Statistical patterns, identified by the co-authors, are indicative of the level of services provided to the population of residential areas (micro-districts/blocks); they will be the subject matter of further scientific discussions to be focused on the substantiation of indicators of comfort and safety of urban environments and multifactorial processes of life activities in biosphere-compatible cities.