When assessing the role and place of statistics in modern digital society, especially from the standpoint of the requirements for the training of analysts working in a wide variety of spheres of social activity [1], it is difficult to ignore a fairly wide range of discussion issues, among which possible approaches to understanding and quantifying statistical thinking are clearly distinguished. This article invites readers to familiarize themselves and discuss the concepts of “statistical” thinking, its meaning in the modern world.

Purpose. This article, using data from three Russian population censuses, examines in detail the dynamics of the family structure of the Russian population. The primary role of families comprising a complete married couple and minor children is substantiated. Based on the changing representation of this family type, a hypothesis is advanced about a slow but persistent decline in the share of these families in the family structure and, to an even greater extent, in the household structure. The authors’ second focus is on single-parent families, both nuclear and complex. The representation of both types is growing, with the growth rate of nuclear families lagging behind that of complex single-parent families.

Materials and methods. The research methodology was based on the combined use of institutional and statistical approaches to analyze changes in households/family structure. The study focused on households and families, and examined the dynamics of family types, expressed as changes in family structure over time. A modified balance sheet calculation of the number of families was implemented using retrospective data, confirming the applicability of this method for short-term forecasts.

Results. The expected trajectories of changes in family structure in Russia are formulated: a slow but continuing decline in the representation of so-called core families, i.e., families with both spouses and minor children; an increase in the proportion of single-parent nuclear families (mother with children, father with children); and an increase in single-parent families of complex composition (with other relatives and non-relatives). Since, in the presence of a complete married couple, cohabitation with relatives has increased only in single-child families, it can be assumed that single-parent family units will dominate the growth of families of complex composition.

Conclusion. The findings can be used to adjust demographic and family policy in Russia: promoting marriage formation and strengthening marital unions, promoting awareness of the value of parenthood and the significance of childhood as a stage of life, adapting the middle and younger generations to the increasing longevity of their grandparents, and developing interactions between the institution of the family, healthcare and education systems, and social institutions supporting families and children.

The purpose of the study is to substantiate economic and statistical models for assessing factors that objectively influence the economic behavior of the region’s population. The relevance of the study is related to the challenges of selecting rationality factors that lead to success. However, market-driven changes in the population’s living conditions have had a negative impact on the processes of reproduction, consumption, and the stratification of society into poor and rich, disrupting fair relations between employees and employers. Hypothesis: the more objective the understanding of one’s own life, activities, and behavior based on people’s actions, deeds, and reactions to changes, the more realistic the models of economic behavior of the population will be. The approaches of scientists who have been awarded Nobel prizes in Economics should be considered as universally recognized models of development. V. Leontiev was awarded for his input-output model (1973). G. Becker was awarded for expanding the scope of microeconomic analysis to include various aspects of human behavior (1992). A. Deaton was awarded for analyzing the problems of consumption, poverty, and social welfare (2015). At the same time, in a free market environment, no one has yet managed to develop a sustainable development model. Each country has its own national development model, which differs from the models of other countries in many ways.

The research materials and methods include economic and statistical models, trends, adaptive and econometric models, extrapolation, comparisons, and generalizations.

Research results: it has been established that factor assessment models include the main components of behavior: personal, demographic, social, economic, and security factors, and “non-economic” variables (moods, emotions, intuitions, and other factors) have been eliminated. The concept of economic and statistical models has been formulated, which is a system of relationships that describes the factors that have a positive impact on population behavior and the reproduction of human, material, and financial capital, and the parameters of which are estimated based on actual data using statistical methods. The study carried out modeling and forecasting of determining models affecting the economic behavior of the population of the subsidized region through trend methods.

Conclusion: the use of economic and statistical models to assess the factors affecting the economic behavior of the population has allowed us to identify the problems that hinder the reproduction of human, material, and financial capital, which affect the improvement of people’s quality of life. The results obtained can be used to substantiate the theoretical and methodological foundations for developing models that directly affect the life and economic behavior of the population.

Research purpose: conducting a statistical assessment of the key profit formation factors in retail chains using the example of PJSC “Magnit” and methods of multivariate statistical analysis. The study aims to identify and quantitatively measure the impact of the main determinants of the company’s financial performance.

Materials and methods. The empirical base of the study consisted of financial reporting data from 26 subsidiaries of PJSC “Magnit” for 2024. A set of econometric methods was applied for data processing: principal component analysis (PCA) to reduce the dimensionality of the initial set of 12 financial indexes and eliminate multicollinearity; multiple regression analysis to assess the influence of the identified factors on net profit; and hierarchical clustering to group subsidiaries by similarity of their financial profiles.

Results. Using the principal component analysis, key factors influencing profit formation were identified, among which the dominant role is played by the results of production and sales activities. The principal component analysis allowed for the identification of two key integral factors, explaining 87,6% of the total variance: f₁ – “Production and sales results” (explained variance 71,5%) and f₂ – “Interest payments” (16,1%). The constructed regression model showed a statistically significant positive influence of factor f₁ on net profit and a significant negative influence of commercial expenses. The influence of factor f₂ was found to be insignificant. Cluster analysis revealed two distinct groups of subsidiaries: a homogeneous cluster of infrastructure companies (4 units) demonstrating high operational efficiency, and a heterogeneous cluster of diversified companies (16 units).

Conclusion. It was established that the main driver of profit for PJSC “Magnit” is the efficiency of operational (production and sales) activities, while the management of interest payments does not have a direct significant impact. The identified cluster structure confirms the necessity of a differentiated approach to managing the subsidiaries. The research results can be used to develop strategies for cost optimization and enhancing the financial sustainability of retail chains.

The relevance of this study is determined, first of all, by the existing lack of research in the literature on the economy of Uzbekistan using social accounts’ matrices and the macroeconomic and sectoral multipliers constructed on their basis. This is due to the lack of available statistics for the supply-use and input-output tables for the entire period of independence of this Central Asian republic until 2018.

Purpose of research: develop a methodology for constructing a social accounts’ matrix for the economy of Uzbekistan based on incomplete official supply-use and input-output tables for 2018. Unlike most studies on other countries, this study also aims to explicitly identify trade and transport margins as a separate structural unit within the social accounts’ matrix, which will allow for a more detailed analysis of the multiplier effects arising in margin-generating sectors during external shocks. As a practical illustration, the response of gross output in the wholesale/retail trade and transport sectors to an exogenous increase in external demand is calculated, and the transmission channels of these effects are analyzed using Stone’s decomposition.

Materials and methods. The study is based on the official, but incomplete, supply-use and input-output tables of Uzbekistan for 2018, compiled according to the SNA standard of 1993. To reconstruct the complete dataset, the author applied the Eurostat methodology, having first determined that the transformation of supply-use tables into input-output tables was carried out according to model B in Eurostat terminology. This allowed the reconstruction of missing tables of the use of domestic and imported goods at basic prices. Particular attention was paid to the correct integration of Financial Intermediation Services Indirectly Measured (FISIM): instead of their redistribution to other accounts, as it is commonly done by most researchers, they were included in the social accounts’ matrix as separate accounts to maintain balance sheet consistency. The constructed matrix is 482x482 in size and includes dedicated blocks for trade and transport margins. Based on it, using Stone’s approach to constructing and decomposing multipliers, multiplier effects for the economy of Uzbekistan were estimated assuming exogeneity of the foreign trade accounts.

Results. The constructed social accounts’ table proved to be internally balanced with high accuracy and can be used for a wide range of applied problems. To illustrate the capabilities of this matrix, gross output multipliers were calculated for the trade and transport sectors under exogenous changes in external demand. It was shown that export-induced output in the trade sector is almost entirely converted into a trade margin, while in the transport sector, this effect is significantly weaker. Stone’s decomposition, which allows for identifying direct, indirect, and cross-channel influences, was used to interpret the results.

Conclusion. The obtained results confirm the analytical significance of explicitly accounting for margins when modeling foreign trade effects. Moreover, the author’s proposed solution is applicable not only to statistics within the system of national accounts of Uzbekistan, but also to any other country with a similar macroeconomic reporting structure.

Purpose of the study. The aim of the study is to develop a decision support system in the form of a Telegram bot, aimed at assessing the investment attractiveness of real estate objects using statistical data analysis and forecasting methods.

Materials and methods. The information base of the study is data from the platform – Central Real Estate Information Agency, containing information about residential real estate objects intended for sale and rent. The methodological base of the study includes methods of statistical data analysis, machine learning, as well as approaches to designing user interfaces in decision support systems. All necessary primary calculations and studies are performed using the functions of the Python programming language. The implementation of the decision support system was carried out in the Google Colab using the pyTelegramBotAPI library.

Results. Information was collected, cleared and pre-processed for 16 cities in Russia, and a study of rental and sale prices for housing was conducted. Using the CatBoostRegressor machine learning model, rental price forecasts for properties put up for sale were obtained, which made it possible to calculate their expected profitability. An analysis was also made of the possibility of using mortgage lending as a tool for increasing investment efficiency. A decision support system has been implemented in the form of a Telegram bot, capable of assessing the profitability of real estate and assisting the user in making decisions based on specified parameters and predictive models. The Telegram bot was tested, and examples of use were demonstrated, confirming the accuracy and usefulness of the calculations obtained.

Conclusion. The developed decision support system can provide recommendations based on the analysis of statistical data of the real estate market and a forecast model. The system is easy to use, focused on private investors, offers real objects presented on the market, automates the process of selection and evaluation of objects, and allows comparing purchase strategies using a mortgage and without attracting additional funds. 

In this article, investor confidence in information is considered to be the main factor affecting the choice of an optimal portfolio of financial instruments under conditions of uncertainty, and determining investor behavior. A problem with modern portfolio theory is that it does not consider individual investor preferences.

The purpose of this study is to revise the traditional concept of evaluating portfolios of financial instruments based on G. Markowitz’s approach. The subject matter is investor behavior that develops in the context of constructing portfolios, evaluating risk components using the W. Sharpe coefficient, and subsequent portfolio modifications due to changes in financial markets or individual investor preferences.

Materials and methods. The theoretical and methodological basis of the research are the approaches developed by domestic and foreign authors, who consider issues in the field of portfolio theory and game-theoretical modelling. The first step is to evaluate Sharpe ratios of financial assets based on real-world data in order to decide whether or not to include them in a portfolio. The second step is clustering alternative financial instruments (low, medium, and high Sharpe ratio values). The third procedure analyzes strategies for constructing portfolios of financial instruments based on Sharpe coefficients. The fourth procedure involves constructing several alternative portfolios in accordance with the presented strategies of the investor. The fifth procedure selects and describes several possible financial market conditions determined by the market index. Following this, the procedure involves constructing a yield matrix, each element of which represents the accumulated return received by the investor if funds are placed in one of the alternative portfolios if financial market implements one of possible conditions. Finally, implementation of the seventh procedure requires determining probabilities of financial market condition determined by market index in order to reduce degree of uncertainty. The last step is to find the optimal portfolio of financial instruments considering the level of investor’s confidence in information, relative to the yield matrix previously constructed and the matrix of risks uniquely generated by it.

Results of the research. The result of the study is a procedural scheme that allows a new approach to designing portfolios of financial instruments and choosing the optimal one, considering the level of investor’s confidence in information. This scheme also reveals the potential for game analysis of how an investor’s confidence in information affects the choice of a financial instrument portfolio in uncertain market conditions.

Conclusion. The results obtained by the author in the form of two games models of interaction between investors and the financial market are useful for further research in financial mathematics. This material can be used for the development of content for professional training of analysts in higher economic education system.