Regional Management as a Factor of Innovation in Russian Regions: Statistical Analysis

2011 ◽  
Author(s):  
konstantin iv grasmik
Keyword(s):  
Statistical Analysis ◽  
Russian Regions ◽  
Regional Management

scholarly journals METHODOLOGICAL DIFFICULTIES OF STATISTICAL ANALYSIS OF THE SCIENTIFIC POTENTIAL OF RUSSIAN REGIONS

2021 ◽  
pp. 60-63
Author(s):  
D. Yu. Znamenskiy
Keyword(s):  
Statistical Analysis ◽  
Systemic Approach ◽  
Russian Regions ◽  
Scientific Organizations ◽  
Scientific Potential ◽  
Quantitative Indicators ◽  
Statistical Indicators ◽  
Methodological Difficulties

The article considers the methodology of the analysis of the scientific potential of the regions. The paper notes the importance of an integrated, systemic approach to understanding of the category of scientific potential. The author emphasizes the importance of quantitative indicators of the scientific potential of the regions, amenable to statistical analysis. The study attempts to analyse the key statistical indicators of the development of science used to assess the scientific potential of the regions. As a rule, the list of such indicators is limited to the number of scientific organizations functioning in the region, the volume of their funding, as well as a number of personnel indicators. At the same time, the author notes the narrowness of the exclusively resource-based approach to the assessment of the scientific potential and the need to take into account its other factors: informational, social, financial, etc.

scholarly journals INTERNATIONAL MIGRATION AND SECURITY IN RUSSIAN REGIONS: STATISTICAL ANALYSIS AND THE EXPERIENCE OF TYPOLOGY BUILDING

2018 ◽  
pp. 13-31
Author(s):  
Омельченко Дарья ◽  
◽  
Максимова Светлана ◽  
Ноянзина Оксана
Keyword(s):  
Statistical Analysis ◽  
International Migration ◽  
Russian Regions

scholarly journals STATISTICAL ANALYSIS OF DEMOGRAPHIC INDICATORS OF THE ROSTOV REGION

2021 ◽  
Vol 2021 (1) ◽  
pp. 16-20
Author(s):  
Vera Shumilina ◽  
Anatoliy Kolesnikov ◽  
Aleksandra Lukiyanova
Keyword(s):  
Sustainable Development ◽  
Statistical Analysis ◽  
The State ◽  
Russian Regions ◽  
The Sustainable Development ◽  
Demographic Indicators ◽  
Rostov Region ◽  
Demographic Processes ◽  
Integral Indicator

The prospects for the sustainable development of Russia in general and the Russian regions in particular are directly or indirectly related to demographic processes. The demographic state of the territories is an integral indicator of all spheres of life, and the level of demographic security reflects the state of stability of the territory to various adverse factors. The purpose of the study is to analyze the state of demographic processes and the level of demographic security as the basis for sustainable development of the Rostov region.

DIFFERENTIATION OF REGIONS OF THE RUSSIAN FEDERATION BY THE LEVEL OF SOCIO-ECONOMIC DEVELOPMENT AND MECHANISMS FOR ITS REDUCTION

2021 ◽  
Vol 2 (3) ◽  
pp. 93-100
Author(s):  
S. K. TOKAEVA ◽  
◽  
A. A. KAISINOV ◽  
◽  
Keyword(s):  
Russian Federation ◽  
Statistical Data ◽  
Regional Inequality ◽  
Russian Regions ◽  
State Management ◽  
Regional Management ◽  
Macroeconomic Indicators ◽  
The Russian Federation ◽  
Degree Of Differentiation ◽  
State Regional

This article deals with the problem of heterogeneity of macroeconomic indicators in individual regions, which is relevant for the state management of regional development. The purpose of the work is to determine the degree of differentiation of Russian regions, identify existing mechanisms to reduce it and evaluate their effectiveness, if necessary, make author's proposals to eliminate this problem. On the basis of official statistical data, it was found that according to the trends of recent years, regional inequality has increased even more, which indicates the inefficiency of state regional management in the Russian Federation. The paper highlights some inefficiently functioning mechanisms for eliminating regional inequality and suggests ways to reduce these disparities.

Statistical analysis of classification

1966 ◽  
Vol 24 ◽  
pp. 188-189
Author(s):  
T. J. Deeming
Keyword(s):  
Multivariate Analysis ◽  
Statistical Analysis ◽  
Classification Scheme ◽  
Analytical Procedure ◽  
Narrow Band ◽  
Scientific Research ◽  
Maximum Amount ◽  
Amount Of Information

If we make a set of measurements, such as narrow-band or multicolour photo-electric measurements, which are designed to improve a scheme of classification, and in particular if they are designed to extend the number of dimensions of classification, i.e. the number of classification parameters, then some important problems of analytical procedure arise. First, it is important not to reproduce the errors of the classification scheme which we are trying to improve. Second, when trying to extend the number of dimensions of classification we have little or nothing with which to test the validity of the new parameters.Problems similar to these have occurred in other areas of scientific research (notably psychology and education) and the branch of Statistics called Multivariate Analysis has been developed to deal with them. The techniques of this subject are largely unknown to astronomers, but, if carefully applied, they should at the very least ensure that the astronomer gets the maximum amount of information out of his data and does not waste his time looking for information which is not there. More optimistically, these techniques are potentially capable of indicating the number of classification parameters necessary and giving specific formulas for computing them, as well as pinpointing those particular measurements which are most crucial for determining the classification parameters.

Quantitative parallel EELS spectrum imaging developed as a new tool in AEM

1992 ◽  
Vol 50 (2) ◽  
pp. 1202-1203
Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance
Keyword(s):  
Statistical Analysis ◽  
Spatial Resolution ◽  
Personal Computer ◽  
Systematic Study ◽  
Present Author ◽  
Chemical Elements ◽  
Detection Limits ◽  
Research Groups ◽  
Quantitative Performance ◽  
Spectrum Imaging

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.

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