Academic literature on the topic 'Russia Statistics'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Russia Statistics.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Russia Statistics"
Belokonnaia, L. "Gender Statistics in Russia." Problems of Economic Transition 43, no. 7 (November 1, 2000): 68–85. http://dx.doi.org/10.2753/pet1061-1991430768.
Full textBelokonnaia, L. "Gender Statistics in Russia." Russian Social Science Review 42, no. 3 (May 2001): 4–21. http://dx.doi.org/10.2753/rss1061-142842034.
Full textMILKA, M., and S. I. CHERNYAVSKIY. "THE RUSSIA-EU PERSPECTIVE: NATIONAL SECURITY AND COUNTERTERRORISM FROM A DIFFERENT ANGLE." Political Science Issues, no. 3(33) part: 9 (December 18, 2019): 293–303. http://dx.doi.org/10.35775/psi.2019.33.3.008.
Full textYamaguchi, Akiyoshi. "The Project of State Statistics Reform by A.M. Zolotarev in the Light of the International Statistical Congresses Decisions." Voprosy statistiki 26, no. 10 (October 28, 2019): 71–79. http://dx.doi.org/10.34023/2313-6383-2019-26-10-71-79.
Full textDementiev, Nicolai. "FOREIGN DIRECT INVESTMENT IN THE RUSSIAN ECONOMY: IN THE TRICK MIRRORS OF STATISTICS." Interexpo GEO-Siberia 3, no. 1 (2019): 94–101. http://dx.doi.org/10.33764/2618-981x-2019-3-1-94-101.
Full textLysova, Alexandra. "Challenges to the veracity and the international comparability of Russian homicide statistics." European Journal of Criminology 17, no. 4 (August 19, 2018): 399–419. http://dx.doi.org/10.1177/1477370818794124.
Full textАбакумов and Stanislav Abakumov. "DEVELOPMENT OF RUSSIAN TOURISM INDUSTRY IN THE CONDITIONS OF IMPORT SUBSTITUTION." Central Russian Journal of Social Sciences 10, no. 5 (October 20, 2015): 205–13. http://dx.doi.org/10.12737/14351.
Full textKirik, Yu V., and P. E. Ratmanov. "The statistics and public health in Russia (end of XIX - early XX centuries): foreign approaches in educational literature." Problems of Social Hygiene, Public Health and History of Medicine 30, no. 6 (December 15, 2022): 1377–82. http://dx.doi.org/10.32687/0869-866x-2022-30-6-1377-1382.
Full textGrigoruk, N. E., and S. A. Galkin. "Implementation of International Standards in Russia's Foreign Trade Statistics." MGIMO Review of International Relations, no. 1(40) (February 28, 2015): 121–27. http://dx.doi.org/10.24833/2071-8160-2015-1-40-121-127.
Full textMahova, Olga A., and Mikhail V. Karmanov. "STATISTICS AND RELIGION IN MODERN RUSSIA." Statistics and Economics, no. 3 (January 1, 2015): 196–99. http://dx.doi.org/10.21686/2500-3925-2015-3-196-199.
Full textDissertations / Theses on the topic "Russia Statistics"
Nosova, Olga. "The attractiveness of foreign direct investment in Russia and Ukraine : a statistical analysis." Universität Potsdam, 1999. http://opus.kobv.de/ubp/volltexte/2007/1207/.
Full textStrugnell, James Paul. "Paintings by numbers : applications of bivariate correlation and descriptive statistics to Russian avant-garde artwork." Thesis, University of St Andrews, 2017. http://hdl.handle.net/10023/10722.
Full textAnikin, Vasiliy. "Skills training and development : Russia in comparative perspective." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/21789/.
Full textFurusawa, Katsuto. "Values and democracy postmaterialist shift versus cultural particularity in Russia, the USA, Britain and Japan /." Thesis, Connect to e-thesis, 2008. http://theses.gla.ac.uk/247/.
Full textPh.D. thesis submitted to the Department of Politics, Faculty of Law, Business and Social Sciences, University of Glasgow, 2008. Includes bibliographical references. Print version also available.
Echlin, M. R. "The statistics of the Russian peasantry in the nineteenth century : a history." Thesis, University of Oxford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305667.
Full textSafonov, Taras Aleksandrovich. "A New Measure of Quality of Life and Its Application in the Regions of the Russian Federation." Thesis, Western Illinois University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1597385.
Full textThe search for a reliable measure of the quality of life (QOL) has long been a heavily discussed issue for many a researcher and a policy analyst. Despite much debate in theoretical and practical circles, there is still no consensus on either what exactly constitutes QOL or on the universal formula to quantify this concept. For instance, the United Nations’ Human Development Index is arguably one of the most well-known indicators of people’s welfare that allows one to compare QOL across countries and regional blocs.
However, the practice of regional policy development and administration shows that government authorities at all levels require a comprehensive tool that would allow them to assess QOL in different regions of a country to develop improved policies aimed at increasing people’s well-being. This is of particular relevance for large federative countries, such as Russia, where official statistics do not employ a spatially comparable aggregate indicator that would measure QOL in the regions.
Therefore, this study attempts to address this issue by following the three research objectives. Firstly, a spatially comparable standardized comprehensive Quality of Life Index (QOLI) is derived for each of the 83 Russian constituent territories based on the data provided by the Russian Federal State Statistics Service for the years 2009-2013. The index is calculated across five dimensions (Physical Well-Being, Decent Standard of Living, Social Security & Inequality, Hospitable Environment, and Education) and incorporates 16 indicators such as Mortality Rates, Average Income, the Gini Coefficient, or Education Attainment, and does not have an analogue in Russian Official Statistics.
The QOLI does not assign weights to its components, letting data “tell their story” in estimating ceteris paribus effects of each of the 16 elements of the QOLI through a series of techniques, which allows to find out what indicator or a group of indicators have the most weight in determining the aggregate index and what parameters affect it only slightly. For instance, the study has found out that health and affordability of living might be the key factors in shaping the level of people’s well-being and that people might be more interested in how their income compares to overall affordability of life in a region rather than what their income amounts to in absolute value. The need for this type of analysis is suggested by practice: policy administrators at various levels usually need to know what factors are most important for reaching higher levels of well-being in order to formulate their policy plans.
The study goes on to elaborate on the derived index methodology, studying spatial and temporal trends in the QOLI that might prevail, for example, in such natural regional groupings as the capital regions or the northern territories. The study also suggests an algorithm of estimating the sustainability of changes in the QOLI, which may prove useful for policy analysts at the step of feasibility research.
Ciotta, Chiara <1996>. "Segmentation of Russian tourists traveling to Italy, Spain and Greece." Master's Degree Thesis, Università Ca' Foscari Venezia, 2022. http://hdl.handle.net/10579/21111.
Full textWhittaker, Edward William Daniel. "Statistical language modelling for automatic speech recognition of Russian and English." Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621936.
Full textSterligov, Boris. "Analyse probabiliste des relations spatiales entre les gisements aurifères et les structures crustales : developpement méthodologique et applications à l'Yenissei Ridge (Russie)." Thesis, Orléans, 2010. http://www.theses.fr/2010ORLE2083.
Full textRecent progresses in geosciences make more and more multidisciplinary data available for mining exploration. This allows developing methodologies to compute predictivity for gold zones by the statistical analysis of variable input parameters. Using newly developed software, the spatial distribution and the topology of polygons (e.g. intrusions) and polylines (e.g. shear zones) are controlled by parameters defined by users (e.g. density, length, surface, etc.). The distance of points of interest (gold deposits) with respect to a given type of objects (polygons or polylines) is given using a probability distribution function. The statistical analyses of output results from the direct modeling process show that i) values of relative surface mean of polygons, relative length mean of polylines, the number of objects and their clustering are critical to statistical appraisals, ii) the validity of the different tested inversion methods strongly depends on the relative importance and on the dependency between the parameters used, and iii) the robustness of the inferred distribution points of interest laws with respect to the quality of the input data. This approach was applied to the geological and geophysical data of the Yenissei ridge of the total area of 75730 km2 for the predictivity mapping of 29 new gold zones with the total area of 1811 km2. The newly developed method allows reducing up to four times of the area of predictivity gold zones, compared with previous studies. For more accurate construction of gold zones, a 3D density model of the Yenisei ridge was constructed. This model is based on surface gravity and aeromagnetic data (numerical grids of 1x1km), ―Batholite‖ and ―Shpate‖ seismic and magnetotelluric profiles, respectively. The 3D density model shows that: a) the Yenissei ridge has a cover-folded structure, formed during a Neopretorozoic collisional event, b) only γNPta Tatarsky-Ayhta granites and shear zones have spatial relationships with gold mineralization
Ferraudo, Guilherme Moraes [UNESP]. "Comparação de modelos mistos, AMMI e Eberhart-Russel via simulação no estudo da interação genótipo x ambiente em cana-de-açúcar." Universidade Estadual Paulista (UNESP), 2013. http://hdl.handle.net/11449/102804.
Full textO Brasil é líder mundial na produção de cana-de-açúcar e o maior exportador mundial de açúcar. O aumento da produtividade da cana-deaçúcar se deve a vários fatores sendo um dos principais a obtenção de novas cultivares e a interpretação da interação genótipo por ambiente (GEI), realizado nos estágios finais de seleção dos programas de melhoramento genético de cana-de-açúcar, torna-se essencial durante o processo de obtenção de novos cultivares. Para poder selecionar os melhores genótipos frente à GEI, os genótipos são avaliados em diversos ambientes (locais e anos) e há o interesse em saber qual o melhor genótipo, baseado no desempenho fenotípico de caracteres de interesse, como, por exemplo, a tonelada de cana por hectare (TCH), que é a principal medida de produtividade de cana-de-açúcar. Sendo a GEI um complicador para o melhorista durante a seleção de genótipos superiores, faz-se necessário a utilização de modelos matemáticos ou estatísticos que consigam identificar de maneira eficiente tais genótipos superiores. Geneticistas e biometristas tem utilizado diversos métodos, porém, não existe um consenso. Assim, neste trabalho, a partir de um estudo de simulação realizado no ambiente computacional R, apresenta-se uma comparação entre três métodos: (i) Eberhart-Russel; (ii) AMMI; (iii) e modelo misto (REML / BLUP). Verificou-se a eficiência de cada método na detecção da GEI e discutiu-se as particularidades de cada um deles do ponto de vista estatístico. No total, simularam-se sessenta e três casos os quais consideraram as mais diversas condições para a introdução da GEI, sendo que, cada um dos três métodos, avaliaram mais do que trinta e quatro milhões e vinte mil dados. Assim, a partir dos resultados encontrados neste trabalho pode-se concluir que cada método detecta a GEI de uma maneira diferente e possui suas limitações...
Brazil is the world leader in sugarcane production, and the largest sugar exporter. Developing new varieties is one of the main factors that contribute to yield increase, and the interpretation of genotype-by-environment interaction (GEI) at the final selection stage is an important consideration in yield estimation. In order to select the best genotypes, varieties are tested in different environments (locations and years), and breeders need to estimate the phenotypic performance for principle traits such as tons of cane yield per hectare (TCH). Since GEI affects breeder selection of superior genotypes it is necessary to use mathematical or statistical models that account for GEI and are able to efficiently identify such genotypes. Geneticists and biometricians have used different methods and there is no clear consensus of the best method. In this paper we present a comparison of three methods, viz. (i) Eberhart-Russel; (ii) AMMI; (iii) and mixed model (REML / BLUP), in a simulation study performed in the R computing environment to verify the effectiveness of each method in detecting GEI, and assess the particularities of each method from a statistical standpoint. In total, 63 cases representing different conditions were simulated, generating more than 34 million data points for analysis by each of the three methods. The results illustrated that each method detects GEI in a different way, and each has some limitations. All three methods detected GEI effectively, but the mixed model showed higher sensitivity. When applying GEI analysis in practice it is important to first verify the assumptions inherent in each model, and respect these limitations in choosing the method to be used
Books on the topic "Russia Statistics"
Arnold, James. Russia market atlas. Vienna, Austria: Economist Intelligence Unit, 1999.
Find full textFederalʹnai͡a sluzhba gosudarstvennoĭ statistiki (Russia). Socio-Demographic Image of Russia: 2010 Russia Population Census. Edited by Dianov M. A. editor. Moscow: Information & Publishing Centre "Statistics of Russia", 2013.
Find full textKingkade, Ward. Population trends: Russia. [Washington, D.C.?]: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1997.
Find full textKingkade, Ward. Population trends: Russia. [Washington, D.C.]: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1996.
Find full textKingkade, William Ward. Population trends: Russia. [Washington, D.C.?]: U.S. Dept. of Commerce, Economics and Statistics Administration, Bureau of the Census, 1997.
Find full textAnne, Pries, ed. Zemstvo statistics: Russia c. 1870-1917. Supplement. Leiden (The Netherlands): Inter Documentation Co., 1992.
Find full textM, Gokhberg L., Mindeli L. Ė, and T͡S︡entr issledovaniĭ i statistiki nauki (Russia), eds. Qualified manpower in Russia. Moscow: Centre for Science Research and Statistics, 2000.
Find full textAgency, International Energy, Energy Charter Secretariat, and Organisation for Economic Co-operation and Development., eds. Russia energy survey, 2002. Paris: OECD/IEA, 2002.
Find full textCipko, Serge. Ukrainians in Russia: A bibliographic and statistical guide. Edmonton: Canadian Institute of Ukrainian Studies Press, University of Alberta, 1994.
Find full textIndia, Export-Import Bank of. Potential for enhancing India's trade with Russia: A brief analysis. Mumbai: Export-Import Bank of India, 2013.
Find full textBook chapters on the topic "Russia Statistics"
Kumo, Kazuhiro. "Population Statistics of Russia: The Russian Empire, the Soviet Union and the Russian Federation." In Demography of Russia, 11–62. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-51850-7_2.
Full textSokolov, Alexander. "Statistics on Information Technology in Russia." In NATO ASI Series, 419–28. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4463-6_22.
Full textStrohe, Hans Gerhard, and Cathleen Faber. "Official Statistics in Russia and the Measurement of the Crisis — Some Remarks on Russian Price Statistics." In Restructuring, Stabilizing and Modernizing the New Russia, 471–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57257-9_22.
Full textFaber, Cathleen, and Hans Gerhard Strohe. "Consumer Prices in Russia and Transforming Official Statistics." In Restructuring, Stabilizing and Modernizing the New Russia, 223–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57257-9_12.
Full textKingston-Mann, Esther. "Statistics, Social Science, and Social Justice: The Zemstvo Statisticians of Pre-Revolutionary Russia." In Russia in the European Context, 1789–1914, 113–39. New York: Palgrave Macmillan US, 2005. http://dx.doi.org/10.1057/9781403982261_8.
Full textMaltseva, Daria, and Ilia Karpov. "Network Studies in Russia: From Articles to the Structure of a Research Community." In Springer Proceedings in Mathematics & Statistics, 259–77. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56829-4_19.
Full textZhegalov, V. A., N. A. Ponomareva, V. A. Saschenkov, and A. V. Razumovskiy. "Burns in Russia: The Statistics and Organization of Specialized Medical Care." In The Management of Burns and Fire Disasters: Perspectives 2000, 145–49. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-009-0361-6_27.
Full textDmitriev, Anton Leonidovich. "Statistics Comes to Russia: Science, Quantitative Analysis, and Shifts in Economic Thinking." In Re-Examining the History of the Russian Economy, 79–95. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75414-7_4.
Full textZherebtsov, Mikhail, and Sergei Goussev. "Tweeting Russian Politics: Studying Online Political Dynamics." In The Palgrave Handbook of Digital Russia Studies, 537–67. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42855-6_30.
Full textMindeli, Levan. "Science and Technology Statistics in Russia: Transformation in Line with the International Standards." In NATO ASI Series, 125–34. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0199-5_12.
Full textConference papers on the topic "Russia Statistics"
Ponomarenko, Alexey. "Reformatting statistical education in Russia: changes in classifications, standards, and programs." In Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2017. http://dx.doi.org/10.52041/srap.17314.
Full textWatanabe, S., M. Fukushima, Yu V. Prohorov, and A. N. Shiryaev. "PROBABILITY THEORY AND MATHEMATICAL STATISTICS." In Seventh Japan–Russia Symposium. WORLD SCIENTIFIC, 1996. http://dx.doi.org/10.1142/9789814532181.
Full textIvanova, I. V. "TO THE 100TH ANNIVERSARY OF STATISTICS IN IRKUTSK REGION." In International scientific-practical conference "Statistics in the strategic development of Russia: facts, assessment, forecasts of social-economic and demographic processes". Publishing House of Irkutsk State University, 2020. http://dx.doi.org/10.26516/978-5-9624-1811-7.2020.21.
Full textZaitseva, Ekaterina, Lyudmila Voronina, and Irina Tuzankina. "Institutionalization of patients’ organizations in Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.170.
Full textMikhaylova, Anna, and Vasilisa Gorochnaya. "Innovation Diffusion in Coastal Agglomerations of Western Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.110.
Full textSamusenko, Dmitry, and Anna Mikhaylova. "Innovation spaces of the European part of Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.133.
Full textBritvina, Irina, Alexey Britvin, and Polina Shumilova. "Cultural barriers to developing migrant entrepreneurship in Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.20.
Full textBoronina, Liudmila, Aleksandr Baliasov, and Iurii Visnevskii. "Innovative potential of youth of industrial regions of Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.18.
Full textAndrei, Izmodenov, and Shaybakova Lyudmila. "FORMATION AND DEVELOPMENT OF EXTERNAL STATE FINANCIAL CONTROL INCONTEMPORARY RUSSIA." In International Conference on Economics, Finance and Statistics. Volkson Press, 2018. http://dx.doi.org/10.26480/icefs.01.2018.107.109.
Full textBagirova, Anna, and Anzhelika Voroshilova. "The prestige of parenting by parents’ assessment: evidence from Russia." In International Days of Statistics and Economics 2019. Libuše Macáková, MELANDRIUM, 2019. http://dx.doi.org/10.18267/pr.2019.los.186.6.
Full textReports on the topic "Russia Statistics"
Panchenko, Liubov, and Andrii Khomiak. Education Statistics: Looking for Case-Study for Modeling. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4461.
Full textTabunov, I. A., T. N. Mikhalenko, L. D. Kuznetsova, A. V. Suetova, and M. A. Shilovskiy. METHODOLOGICAL RECOMMENDATIONS FOR WORKING WITH CHILDREN IN A SOCIALLY DANGEROUS SITUATION. Cherepovets State University, December 2022. http://dx.doi.org/10.12731/er0619.03122022.
Full textTOKAREV, YURY. THE MULTIDIMENSIONAL STATISTICAL ANALYSIS OF HOUSING CONSTRUCTION IN RUSSIA. Science and Innovation Center Publishing House, 2020. http://dx.doi.org/10.12731/2070-7568-2020-1-2-195-203.
Full textPALIY, T., and A. BAGIYAN. CHARACTERISTIC OF A TEACHER-PHILOLOGIST’S PROFESSIONAL PERSONALITY THROUGH THE PRISM OF AXIOLOGY. Science and Innovation Center Publishing House, 2021. http://dx.doi.org/10.12731/2658-4034-2021-12-4-2-48-58.
Full textOSIYANOVA, A., and D. SARKINA. LEXICAL AND GRAMMATICAL TRANSFORMATIONS IN THE SOCIO-POLITICAL TEXTS TRANSLATION (ON THE MATERIAL OF THE US PRESIDENT J. BIDEN’S SPEECHES). Science and Innovation Center Publishing House, 2022. http://dx.doi.org/10.12731/2077-1770-2022-14-2-3-14-22.
Full textТитаренко, Д. М. Геноцид єврейського населення на Донеччині під час нацистської окупації: деякі дискусійні аспекти проблеми. ДонНУ, 2008. http://dx.doi.org/10.31812/123456789/6496.
Full textMurphy, Keire, and Anne Sheridan. Annual report on migration and asylum 2022: Ireland. ESRI, November 2023. http://dx.doi.org/10.26504/sustat124.
Full textShynenko, Mykola, and Olga Pinchuk. Activity of users of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" during crisis events. Institute for Digitalization of Education, 2022. http://dx.doi.org/10.33407/lib.naes.733438.
Full textHalych, Valentyna. SERHII YEFREMOV’S COOPERATION WITH THE WESTERN UKRAINIAN PRESS: MEMORIAL RECEPTION. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11055.
Full text