Statistical Literacy as a Way to Achieve Social Consensus

The maintenance of civil peace and harmony in the Russian state from time immemorial has been defined as a priority that allows maintaining the integrity of both state and territorial. Global processes taking place in the world, epidemic waves of viruses, incessant local wars, diligent attempts to separate people and peoples bring to the fore the need to consolidate society in order to ensure the national security of the country. In this context, the importance of statistics increases, which significantly affects the perception of the dominant values by society, forms the attitude of people to the state policy being pursued. At the same time, the understanding of statistical information (figures, data) in a number of cases does not correspond to reality, making it difficult to adequately assess the existing situation, which is associated with an insufficient level of statistical literacy of the population, officials and specialists in various fields of activity.

GIS and Geo-Positioning Developments in Coping With the Pandemic

This chapter deals with some technical aspects of the spatial strategy for overcoming the huge challenges posed by the pandemic. The focus of this chapter is to highlight the use of GIS tools and positioning technologies in diverse contexts to manage the threat of COVID-19. For this task, three stages of analysis are proposed. In a first preventive stage, some governments applied socioeconomic criteria drawn from existent statistical information to spatially identify the areas with a clear predisposition toward the accelerated spread of the contagion. In a second stage, when the pandemic fully reached a rapid pace of expansion and lockdown measures became necessary, the technologies helped to monitor the most affected areas and to establish a dashboard deployment for visualizing the severity of the catastrophe. In the third stage, after the establishment of control and mobility protocols, different governments resorted to mobile phone positioning as a resource for monitoring quarantine compliance and recognizing if social group behavior entailed any evident risk or spread.

Development of higher education in the regions of Russia: pedagogical staff number

This research aimed to assess the indicators that characterize the number of teaching staff at universities and other higher education institutions (HEIs) in the regions of Russia. These indicators were: (1) the number of teachers per thousand working-age residents of each of the regions, (2) the average number of teachers per HEI in the region, (3) the proportion of teachers who have a Doctor of Science (DSc) and a Doctor of Philosophy (PhD) degree in the number of teachers working in HEIs in the region, and (4) the number of students per teacher working in HEIs. We used official statistical information of 82 regions of Russia. We found that, on average, there are slightly more than two teachers working in HIEs per thousand working-age residents. The average number of teachers per HIE in Russia is 158. In universities, the average number of students per teacher is more than 20. The proposed methodological approach and the obtained results are a scientific novelty, since the assessment of regional characteristics of the number of teaching staff in the regions of Russia has not been carried out before.

Amateur football map (4th league) from Romania generated by the coronavirus (COVID-19) in the pre-pandemic season (2019/2020)

After the 2nd World War, for the first time after 7 decades, sports in general, and amateur football in particular, are facing a new global challenge generated by the coronavirus (COVID-19) pandemic. Pre-pandemic football season 2019/2020 held on the field only for the first part (690 teams; 781 games), was suspended at the beginning of March, 2020. This situation generated an uncertain 5-month break until the first official games in play-offs (1-9 August, 2020) in wich only 46 teams (6.6%) in total actually participated. In a state of global uncertainty, to the suggestion of RFF, the 42 county football associations were “invited” to identify new solutions in order to “finalize the season”, by declaring, or not, a champion team, another team for the national phase of Romania’s Cup and a county representative for the 3rd league play-off. With the help of statistical information provided by county structures, with the spatial analysis of statistical data reported and analyzed on local and regional level, were analyzed the created situations and, especially, the consequences generated by the pandemic situation upon amateur football in Romania illustrated by maps.

Amateur football map (4th league) from Romania generated by the coronavirus (COVID-19) in the pre-pandemic season (2019/2020)

After the 2nd World War, for the first time after 7 decades, sports in general, and amateur football in particular, are facing a new global challenge generated by the coronavirus (COVID-19) pandemic. Pre-pandemic football season 2019/2020 held on the field only for the first part (690 teams; 781 games), was suspended at the beginning of March, 2020. This situation generated an uncertain 5-month break until the first official games in play-offs (1-9 August, 2020) in wich only 46 teams (6.6%) in total actually participated. In a state of global uncertainty, to the suggestion of RFF, the 42 county football associations were “invited” to identify new solutions in order to “finalize the season”, by declaring, or not, a champion team, another team for the national phase of Romania’s Cup and a county representative for the 3rd league play-off. With the help of statistical information provided by county structures, with the spatial analysis of statistical data reported and analyzed on local and regional level, were analyzed the created situations and, especially, the consequences generated by the pandemic situation upon amateur football in Romania illustrated by maps.

Typology of Municipalities to Monitor Their Socio-Economic Development

One of the urgent tasks of the state policy of spatial development is the introduction of a permanent system for monitoring the socio-economic development of municipalities (at least at the level of municipal and districts), for which, as stated in the article, it is necessary to develop typologies of municipalities. It is advisable to generalize and analyze statistical information on municipalities on the basis of its automatic processing for different types of territories. The article analyzes the existing experience of the EU and the OECD in the typology of regions comparable to Russian municipal districts, and also summarizes the experience accumulated in Russia in the typologization of territories – municipalities in general, cities. It is shown that the basic typology can and should be based on an assessment of the settlement system – the ratio of urban and rural population, population density, the presence of a large urban center or proximity to it. Additionally, it is also important to take into account natural and climatic conditions, geographical location, sustainable economic specialization, and administrative status.

Early Dropout Prediction in Online Learning of University using Machine Learning

Recently, most universities plan to open or open online learning courses, but the problem of dropout of online learning is still a problem for universities. Online learning has the advantage of being able to receive education anytime, anywhere, but it is true that the dropout rate is higher than offline classes because you have to manage and control your own study time without the help of a professor or manager. Therefore, it is very important for professors and managers to support students in a timely act to avoid the risk of dropout of university online classes. This study used the access log data recorded in the Learning Management System (LMS) and the learner's statistical information and calculated data, and aims to present predictive algorithms suitable for online learning dropout early prediction systems at universities. This study features a 7-year online learning history log data recorded in the Cyber University LMS system to overcome the data count limitations of existing studies and predict the risk of drop-out during the learning period. The characteristics of the data you utilized were used to validate the availability of predictive models by applying learner statistical information, number of system connections, number of lectures, previous semester grade data, machine learning based decision tree, arbitrary forest (RF), support vector machine (SVM) and deep learning (DNN). Studies show that random forest (RF) algorithms have the best prediction and performance, and deep learning algorithms also apply to learning management (LMS) systems.

Technical indicators of modern trawlers

The article identifies the problem of the lack of up-to-date publicly available statistical information on the technical and economic performance of modern fishing vessels, including foreign mining vessels, which entails serious restrictions on the choice of a prototype, from which domestic authors are forced to use outdated indicators of ship designs built in the second half of the XX century. The methods of obtaining the necessary information using the open databases of the Global Fishing Watch organization are presented. The methods of the organization's work with information and the characteristics of some databases are described. The data has been processed for further use. According to one of the fishing criteria, the most effective trawlers of 2020 were selected. Thanks to the obtained statistics on the operation of trawlers, it was possible to obtain many technical indicators of the vessels ' operation: the operating mode, the structure and duration of the fishing voyage, the form of fishing organization, the balance of calendar time. As the statistics are processed, the results are analyzed. The observations made are described: about the round-the-clock operation mode; about the duration of storming; about the associated fishing. The obtained indicators were compared with the indicators of trawler factories in 1969. The necessity of continuing the study of the main technical and economic indicators of modern fishing vessels: income, expenses, profit is justified.

ANALYSIS OF THE FINANCIAL CONDITION OF THE DEBTOR-CITIZEN WHEN INTRODUCING BANKRUPTCY PROCEDURES: TECHNOLOGY AND PROBLEMS OF CONDUCTING

Currently, many citizens actively resort to such an institution of a market economy as insolvency (bankruptcy). The effectiveness of this procedure’s carrying out depends on a number of factors, among which are the level of qualification, experience and knowledge of the arbitration manager, the debtor-citizen’s willingness to cooperate and the quality of methodological support of the process itself. The article discusses the methodological aspects of conducting the analysis of the financial condition of the debtor-citizen, describes the technology of adapting the official methodology of financial analysis applied to legal entities, identifies problems in the process of conducting such an analysis, and suggests the main directions for its improvement. Statistical information on the number and dynamics in the number of citizens declared bankrupt is presented. The author carried out systematization of information sources that underlie the financial analysis, and identified incomplete and unreliable sources that do not give arbitration managers the opportunities to draw adequate and correct conclusions. The study highlights the problem of analyzing the possibility of restoring the debtor-citizen's solvency, as this directly affects the possibility of introducing a bankruptcy rehabilitation procedure – restructuring the debtor's debt. The article examines the features of calculating the indicators that underlie the debtor's analysis in order to identify signs of intentional and fictitious bankruptcy; it reflects the methodological aspects of adapting the official methodology. The existing problems in carrying out the financial analysis of the debtor-citizen are formulated.