The Task of Improving the University Ranking Based on the Statistical Analysis Methods

2021 ◽  
pp. 65-75
Author(s):  
A. Mikryukov ◽  
M. Mazurov
Keyword(s):  
Statistical Analysis ◽  
University Ranking ◽  
Analysis Methods ◽  
The University ◽  
Statistical Analysis Methods

The economy of the Chukotka Autonomous Okrug: On the path from monodependence to diversification

2020 ◽  
Vol 18 (4) ◽  
pp. 662-674
Author(s):  
S.G. Serikov
Keyword(s):  
Economic Development ◽  
Statistical Analysis ◽  
Gross Regional Product ◽  
Key Factors ◽  
Economic Problems ◽  
Analysis Methods ◽  
Socio Economic Development ◽  
Regional Product ◽  
Statistical Analysis Methods

Subject. This article explores the changes in the economic development of the Chukotka Autonomous Okrug during the Soviet and post-Soviet periods. Objectives. The article aims to identify trends and features of the socio-economic development of the Chukotka Autonomous Okrug. Methods. For the study, I used the comparative, computational, constructive, and statistical analysis methods. Results. The article reveals key factors in the growth of the Chukotka Autonomous Okrug's gross regional product and the economic challenges to the region. As well, the article considers and proposes some possible options for further socio-economic development of the Okrug. Conclusions. The Okrug's current socio-economic problems are caused by not objective reasons only, but subjective factors, as well.

RISK FACTORS FOR THE DEVELOPMENT OF INITIAL MANIFESTATIONS OF ATHEROGENIC CARDIOVASCULAR DISEASES IN PERSONNEL OF CHEMICALLY HAZARDOUS FACILITIES

2017 ◽  
pp. 2-7 ◽  
Author(s):  
V. A. Gorichny ◽  
D. Yu. Serdukov ◽  
A. V. Yazenok ◽  
A. V. Nosov ◽  
G. G. Zagorodnikov ◽  
...  
Keyword(s):  
Risk Factors ◽  
Statistical Analysis ◽  
Cardiovascular Diseases ◽  
Organophosphorus Compounds ◽  
Atherogenic Dyslipidemia ◽  
Chemical Weapons ◽  
Analysis Methods ◽  
High Incidence ◽  
And Control ◽  
Statistical Analysis Methods

An outpatient examination of 530 employees engaged in work with chemical weapons related to organophosphorus compounds at chemically hazardous facilities was carried out. Risk factors for the development of cardiovascular diseases of atherogenic etiology among personnel of the facilities were studied in relation to the type of work performed using statistical analysis methods. When assessing the lipidogram, a high incidence of atherogenic dyslipidemia in a group of personnel involved in the storage of chemical weapons was found out in comparison with a group of people engaged in the destruction and control of chemical weapons (73.1 vs 61.2 vs 59.6%, p

scholarly journals Quantification and Statistical Analysis Methods for Vessel Wall Components from Stained Images with Masson's Trichrome

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146954 ◽  
Author(s):  
Pablo Hernández-Morera ◽  
Irene Castaño-González ◽  
Carlos M. Travieso-González ◽  
Blanca Mompeó-Corredera ◽  
Francisco Ortega-Santana
Keyword(s):  
Statistical Analysis ◽  
Vessel Wall ◽  
Analysis Methods ◽  
Wall Components ◽  
Statistical Analysis Methods

Statistical analysis methods for transient flows – the dam-break case

2018 ◽  
Vol 57 (5) ◽  
pp. 688-701 ◽  
Author(s):  
Rui Aleixo ◽  
Sandra Soares-Frazão ◽  
Yves Zech
Keyword(s):  
Statistical Analysis ◽  
Dam Break ◽  
Transient Flows ◽  
Analysis Methods ◽  
Statistical Analysis Methods

scholarly journals Proposals for university promoting in QS rating based on the methods of statistical analysis

2020 ◽  
Vol 17 (1) ◽  
pp. 35-43
Author(s):  
A. A. Mikryukov ◽  
M. S. Gasparian ◽  
D. S. Karpov
Keyword(s):  
Factor Analysis ◽  
Statistical Analysis ◽  
Performance Indicators ◽  
Factor Model ◽  
Reference Group ◽  
Latent Factors ◽  
University Ranking ◽  
Factors Affecting ◽  
University Performance ◽  
The University

The purpose of the study. The purpose of the study is to develop scientifically based proposals to increase the university performance indicators in the international institutional rating QS to the required values, taking into account the presence of a combination of latent (hidden) factors, the degree of achievement of the set values of the basic indicators and, as a result, the university ranking level.Materials and methods. To achieve this goal, methods of statistical analysis (correlation-regression and factor analysis) were used, which made it possible to identify the degree of influence of latent factors on basic indicators and the main indicator (rating functional). During the study, the following tasks were solved: identification of latent factors affecting the basic indicators of the university, an assessment of their significance and degree of influence on the basic indicators, as well as their grouping. Based on the results of the correlation - regression and factor analysis, measures are formulated to achieve the specified values of the QS University institutional rating indicators.Results. An approach to solving the problem of providing conditions for achieving the required values of university performance indicators in the international institutional ranking QS using models developed based on the methods of correlation-regression and factor analysis is proposed. Estimates of the relationship of indicators and university ranking based on the methods of correlation and regression analysis are obtained. A comparative analysis of the results obtained at the universities of the reference group is made. The problem of identifying factors that influence the change in the values of indicators is solved; the degree of this influence is assessed. Based on the results obtained, reasonable proposals have been developed to achieve the required values of the basic indicators and the rating functional of the university.Conclusion. The results obtained in the course of the study made it possible to justify the measures necessary to solve the problem of achieving the specified performance indicators of the university. Based on the correlation model, correlation dependencies between the rating functional and basic indicators are obtained. Interpretation of the results of factor analysis allowed us to identify a set of factors that have a significant impact on the basic indicators. It is shown that measures to achieve the specified indicators must be carried out taking into account the revealed correlation dependencies between factors and basic indicators, as well as the interpretation results of the developed factor model.

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