Determination of the minimum number of periods for assessing the sustainable development indices of the EU countries using the methods of ordinal statistics

Authors

DOI:

https://doi.org/10.30837/ITSSI.2024.27.215

Keywords:

law of distribution; quantity of assessment periods; statistical information; identification; mathematical expectation; ordinal statistics; dispersion; index of sustainable development.

Abstract

The subject matter of the article is the process of assessing the sustainable development indices of the European Union countries. The goal of the article is to develop a methodology for determining the number of periods for which it is necessary and sufficient to assess the sustainable development indices of states. The article results the following task: to develop a methodology for determining the law of distribution of random variables of sustainable development indices. Determination of the minimum number of periods for assessing the sustainable development indices of the European Union countries. Methods used: parametric and ordinal statistics. The following results are obtained: parametric and non-parametric methods of statistics, their advantages and disadvantages are considered. Various methods of estimating the distribution function for small samples, in particular the method of rectangular contributions and the method of uncertainty reduction are analysed. Particular attention is paid to the problem of changing the law of scattering of quality indicators when changing the conditions of technology. A graph-analytical method for identifying the law of distribution of random variables based on a small amount of statistical information is proposed. For this purpose, the theory of ordinal statistics was used. A step-by-step methodology for identifying the law of distribution of random variables using 10 ordered values has been developed. The mathematical expectations of ordinal statistics for three distribution laws are proposed. A methodology for determining the number of periods for assessing the indices of sustainable development of countries using ordinal statistics is developed. The study is based on the analysis of statistical data for the last ten years and their ordering in ascending order. The mathematical expectations of ordinal statistics are used to select appropriate distribution laws. Given the limited information available when working with small samples, the article proposes a methodology that allows obtaining the maximum amount of information from the available data. The developed approach makes it possible to take into account the uncertainty of the phenomenon under study and make informed decisions based on statistical analysis. Conclusions: based on the knowledge of the law of distribution, a methodology for determining the minimum number of periods for assessing the sustainable development indices of the European Union countries is proposed. Testing of the methodology on real numerical data has confirmed that the minimum number of periods is seven, provided that the distribution law follows the normal law.

Author Biographies

Olena Cherniak, Educational and Scientific Institute "Ukrainian Engineering Pedagogics Academy" V. N. Karazin Kharkiv National University

PhD (Engineering Sciences), Associate Professor, Associate Professor at the Department of Automation, Metrology and Energy Efficient Technologies

Ihor Bahaiev, Educational and Scientific Institute "Ukrainian Engineering Pedagogics Academy" V. N. Karazin Kharkiv National University

Postgraduate Student at the Department of Automation, Metrology and Energy Efficient Technologies

Oleh Katrych, National Aerospace University "Kharkiv Aviation Institute"

PhD (Engineering Sciences), Doctoral Candidates at the Department of Mechatronics and Electrical Engineering

Oleksandr Teslov, National Aerospace University "Kharkiv Aviation Institute"

Postgraduate Student at the Department of Mechatronics and Electrical Engineering

Olha Kosychenko, National Aerospace University "Kharkiv Aviation Institute"

Senior Lecturer at the Department of Mechatronics and Electrical Engineering

Viacheslav Shevchenko, National Aerospace University "Kharkiv Aviation Institute"

Postgraduate Student at the Department of Mechatronics and Electrical Engineering

References

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References

Liu, Y., Huang, B., Guo, H. (2023), "A big data approach to assess progress towards Sustainable Development Goals for cities of varying sizes", Commun Earth Environ, No. 4 (66). DOI: https://doi.org/10.1038/s43247-023-00730-8

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Sabia, G., Mattioli, D., Langone, M., Petta, L. (2023), "Methodology for a preliminary assessment of water use sustainability in industries at sub-basin level", Journal of Environmental Management, Vol. 343, P. 118–163, DOI: https://doi.org/10.1016/j.jenvman.2023.118163

Toniolo, S., Pieretto, C., Camana, D. (2023), "Improving sustainability in communities: Linking the local scale to the concept of sustainable development", Environmental Impact Assessment Review, Vol. 101, P. 107–126. DOI: https://doi.org/10.1016/j.eiar.2023.107126

Correia, E., Garrido-Azevedo, S., Carvalho, H. (2023), "Supply Chain Sustainability: A Model to Assess the Maturity Level", Systems, No. 11(2):98. DOI: https://doi.org/10.3390/systems11020098

Trishch, R., Nechuiviter, O., Dyadyura, K., Vasilevskyi, O., Tsykhanovska, I., Yakovlev, M. (2021), "Qualimetric method of assessing risks of low quality products", MM Science Journal, 2021-October, P. 4769–4774. DOI: https://doi.org/10.17973/MMSJ.2021_10_2021030

Ginevičius, R., Trišč, R., Remeikienė, R., Zielińska, A., Strikaitė-Latušinskaja, G. (2022), "Evaluation of the condition of social processes based on qualimetric methods: The COVID-19 case", Journal of International Studies, No. 15(1), P. 230–249. DOI: https://doi.org/10.14254/2071-8330.2022/15-1/15

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Jakobsson, U., Westergren, A. (2005), "Statistical methods for assessing agreement for ordinal data", Scandinavian Journal of Caring Sciences, No. 19, P. 427–431. DOI: https://doi.org/10.1111/j.1471-6712.2005.00368.x

Moffat, R. J. (June 1985), "Using Uncertainty Analysis in the Planning of an Experiment", ASME, No. 107(2), P. 173–178. DOI: https://doi.org/10.1115/1.3242452

Robbins, H. (1992), An Empirical Bayes Approach to Statistics, In: Kotz, S., Johnson, N. (eds) Breakthroughs in Statistics, Springer Series in Statistics, Springer, New York, NY. DOI: https://doi.org/10.1007/978-1-4612-0919-5_26

Steiner, S., MacKay, R. (2005), Statistical engineering, Quality Press. 319 p.

Wald, A. (2004), Sequential analysis, Courier Corporation. 212 p.

David, H. (1970), Order statistics, John wiley and sons, 272 p.

Organisation for Economic Co-operation and Development (OECD), available at: https://www.oecd.org/ (last accessed: 28.02.2024).

Published

2024-07-02

How to Cite

Cherniak, O., Bahaiev, I., Katrych, O., Teslov, O., Kosychenko, O., & Shevchenko, V. (2024). Determination of the minimum number of periods for assessing the sustainable development indices of the EU countries using the methods of ordinal statistics. INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, (1 (27), 215–225. https://doi.org/10.30837/ITSSI.2024.27.215

Issue

Section

MODERN ENTERPRISE MANAGEMENT TECHNOLOGIES