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1

Sibirskaya, Elena V., Lyudmila V. Oveshnikova, Lilia A. Mikheykina, and Innara R. Lyapina. Economic Systems Analysis: Statistical Indicators. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-91247-9.

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2

International Conference on Environmental Indices Systems Analysis Approach (1st 1997 Saint Petersburg, Russia). Environmental indices systems analysis approach. Oxford: EOLSS, 1999.

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3

Nicholson, M. Attitude Determination Error Analysis System (ADEAS) mathematical specification document. [Greenbelt, Md.]: Goddard Space Flight Center, 1988.

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4

Okubo, Yoshiko. Bibliometric indicators and analysis of research systems: Methods and examples. Paris: OECD, 1997.

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5

Kenna, James G. The Significant Indicator Workload Analysis System: Review and recommendations. [Salt Lake City, Utah: Bureau of Land Management, Utah State Office], 1987.

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6

Political atlas of the modern world: An experiment in multidimensional statistical analysis of the political systems of modern states. Chichester, West Sussex: Wiley-Blackwell, 2010.

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7

Kielmann, Arnfried A. Assessing district health needs, services, and systems: Protocols for rapid data collection and analysis. Nairobi, Kenya: African Medical and Research Foundation, 1991.

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8

Lefkovits, Ivan. Limiting dilution analysis of cells of the immune system. 2nd ed. Oxford [England]: Oxford University Press, 1999.

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9

Minobrnauki, Rossiyskoy. Finance and Financial analysis. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1242227.

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The textbook systematizes basic knowledge in the field of finance, financial analysis and financial management, presented in their direct relationship and significance from the point of view of evaluation, diagnosis, forecasting and monitoring of the continuity of the organization's activities. It includes seven chapters grouped into three sections. The first section is devoted to the theoretical foundations of the organization's financial management, stakeholders and sources of the organization's activities. The second section discusses the basics of financial analysis, providing knowledge of the main directions, information base and methods of financial analysis, as well as allowing them to be applied reasonably, calculate and evaluate analytical indicators, determine the impact of globalization processes, various macro-and microfactors on the financial condition of the organization. The third section contains the basics of financial management, providing an understanding of the essence of the financial mechanism of the organization and algorithms for justifying decisions in the field of financial management. It complies with the federal state educational standards of higher education of the latest generation and provides the formation of basic competencies in the field of finance, financial management and financial analysis. For bachelor's, specialist's and master's students studying in the field of Economics, the system of additional professional education, training centers for advanced training of auditors and other financial market specialists, as well as for individual preparation of applicants for qualification certification and passing qualification exams.
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10

Common country assessment of Lesotho: A country-based process for reviewing and analysing the national development situation and identifying key issues as a basis for advocacy and policy dialogue : December 2004 report. Maseru]: United Nations System in Lesotho, 2004.

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11

Saunders, David. Manual: MBTI expanded analysis report : a scoring system for form J of the Myers-Briggs type indicator. Palo Alto, CA: Consulting Psychologists Press, 1989.

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12

Terehin, Valeriy, and Viktor Chernyshov. Efficiency and effectiveness of the penitentiary system: assessment and planning. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1079434.

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The issues of setting goals, planning and forming a system of indicators of the effectiveness and efficiency of the penal system are considered. The criteria for determining the goals-tasks that are adequate to the public goals of the system are justified. Quantitative indicators corresponding to the criteria were developed, based on the contribution of the criminal justice System to reducing the socio-economic losses of society from recidivism. The contribution of the system is determined by changes in the criminal potential of convicted persons during the period of serving a sentence under a court sentence. Criminal potentials are estimated by predictive values of the aggregate of three groups of characteristics of the criminal potential of convicts, determined by the stages of the cycle of recidivism. The practical results of the use of sound methods and developed tools are based on the use of a significant amount of empirical data on the institutions of the criminal justice system and its systematic expert and statistical analysis. The monograph is a generalization and development of the works carried out by the authors during 2012-2017 in the process of preparing masters of Management for the penal system. It is intended for managers and specialists of the bodies and institutions of the Criminal Justice System, researchers, teachers of higher educational institutions who train specialists for law enforcement agencies.
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13

1962-, Dahlquist Julie R., ed. Technical market indicators: Analysis & performance. New York: Wiley, 1999.

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14

Keith, Schap, ed. Seven indicators that move markets. New York: McGraw-Hill, 2003.

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15

Asia Pacific Energy Research Centre (Nihon Enerugī Keizai Kenkyūjo). Energy efficiency indicators: A study of energy efficiency indicators in APEC economies. Tokyo, Japan: Asia Pacific Energy Research Centre, Institute of Energy Economics, Japan, 2001.

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16

Manandhar, Raju. Longitudinal study on system indicators. Kathmandu: Tribhuvan University, Research Centre for Educational Innovation and Development (CERID), 2009.

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17

J, Pring Martin, ed. The definitive guide to momentum indicators. New York: Marketplace Books Inc., 2009.

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18

D, Stevenson William, and Stevenson William D, eds. Power system analysis. New York: McGraw-Hill, 1994.

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19

Linear system analysis. New York: Wiley, 1987.

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20

Massacutee, Robert P. KEY analysis system. Golden, Colo: U.S. Dept. of the Interior, U.S. Geological Survey, National Earthquake Information Center ; [Denver, Colo., 1994.

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21

Masse, Robert P. KEY analysis system. Golden, Colo: U.S. Dept. of the Interior, U.S. Geological Survey, National Earthquake Information Center ; [Denver, Colo., 1994.

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22

Power system analysis. 2nd ed. New York: Wiley, 1986.

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23

Massé, Robert P. KEY analysis system. Golden, Colo: U.S. Dept. of the Interior, U.S. Geological Survey, National Earthquake Information Center ; [Denver, Colo., 1994.

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24

Murty, P. S. R. Power System Analysis. New Delhi: BS Publications, 2007.

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25

Power system analysis. 3rd ed. [United States]: PSA Pub., 2010.

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26

Das, J. C. Power System Analysis. New York: Marcel Dekker, Inc., 2003.

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27

Saadat, Hadi. Power system analysis. Boston: WCB/McGraw-Hill, 1999.

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28

Murthy, P. S. R. Power system analysis. Hyderabad [India]: BS Publications, 2007.

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29

Gross, Charles A. Power system analysis. 2nd ed. New York: Wiley, 1986.

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30

Grady, Jeffrey O. System requirements analysis. New York: McGraw-Hill, 1993.

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31

Schellnhuber, Hans-Joachim, and Volker Wenzel, eds. Earth System Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-52354-0.

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32

Nagsarkar, T. K. Power system analysis. New Delhi: Oxford University Press, 2007.

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33

Tainer, Evelina M. Using economic indicators to improve investment analysis. New York: Wiley, 1993.

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34

Using economic indicators to improve investment analysis. 2nd ed. New York: Wiley, 1998.

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35

Using economic indicators to improve investment analysis. 3rd ed. Hoboken, N.J: Wiley, 2006.

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36

Tainer, Evelina M., ed. Using Economic Indicators to Improve Investment Analysis. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781119201557.

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37

Tainer, Evelina M. Using Economic Indicators to Improve Investment Analysis. New York: John Wiley & Sons, Ltd., 2006.

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38

DeMark indicators. New York: Bloomberg Press, 2008.

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39

Wils, Annababette. Regional education analysis for Namibia. Windhoek: Republic of Namibia, 2012.

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40

1953-1999, Evans Owen, ed. Macroprudential indicators of financial system soundness. Washington, DC: International Monetary Fund, 2000.

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41

Hilbers, Paul, Alfredo Leone, Mahinder Gill, and Owen Evens. Macroprudential Indicators of Financial System Soundness. Washington, D.C.: International Monetary Fund, 2000. http://dx.doi.org/10.5089/9781557758910.084.

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42

Country analysis: Understanding economic and political performance. Farnham Surrey: Gower Pub., 2011.

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43

Dawood, Shah S., Butt Sarwat, and Academy of Educational Planning and Management (Pakistan), eds. Comparative analysis of educational indicators, 2003-04 & 2004-05. Islamabad: Academy of Educational Planning and Management, Ministry of Education, 2006.

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44

Sibirskaya, Elena V., Lyudmila V. Oveshnikova, Lilia A. Mikheykina, and Innara R. Lyapina. Economic Systems Analysis: Statistical Indicators. Springer, 2019.

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45

Sibirskaya, Elena V., Lyudmila V. Oveshnikova, Lilia A. Mikheykina, and Innara R. Lyapina. Economic Systems Analysis: Statistical Indicators. Springer, 2018.

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46

World Health Organization, Colombo, Sri Lanka., ed. Poverty, transition, and health: A rapid health system analysis, March 2002. Colombo, Sri Lanka: World Health Organization, 2002.

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47

Organisation for economic co-operation and development. Education at a Glance Analysis (Indicators of Education Systems). Organization for Economic, 1996.

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48

Rahat, Gideon, and Ofer Kenig. Indicators of Political Personalization. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198808008.003.0007.

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Ten indicators of political personalization, covering all of its types and subtypes, are presented in this chapter. The analysis starts with the institutional personalization of both governmental (electoral systems and executives) and nongovernmental institutions (leadership selection and candidate selection in political parties). It then turns to indicators of media personalization, of both the uncontrolled (news coverage of politics) and the controlled type (unmediated messages). Finally, the chapter looks at indicators of personalization in the behavior of politicians (legislators’ behavior) and of voters. The logic and significance of each indicator is examined, as well as its advantages and limitations; and trends developed over time are presented country by country. Potential indicators that are not used are also mentioned and their exclusion is explained.
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49

Gandrud, Christopher. The Reproducibility of Governance Indicators. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198817062.003.0009.

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Reproducibility is a core tenant of scientific enquiry, including the study of governance and government outputs. Having full access to the data and procedures that researchers used to study a phenomenon is vital for being able to understand and trust their findings. This chapter sets out best practices for the reproducibility of governance indicators. For a governance indicator project to be ‘really reproducible’, the full data as well as data gathering and analysis procedures should be easily and persistently accessible. Indicator development should be fully documented, especially via a version control system. The chapter surveys the status quo level of reproducibility among prominent governance indicator projects. While most had some reproduction material available, none were really reproducible. The chapter concludes with recommendations, including calling for a shared governance indicator hosting service that focuses on encouraging reproducibility.
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50

Jobman, Darrell R. Handbook of Technical Analysis: A Comprehensive Guide to Analytical Methods, Trading Systems and Technical Indicators. McGraw-Hill Companies, 1994.

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