Analysis of the regression model of the enterprise’s financial activity by research on residual error

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T.Beridze,, Kryvyi Rih National University, Kryvyi Rih, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.Cherep,, Zaporizhzhia National University, Zaporizhzhia, Ukraine

Z.Baranik,, Kyiv National Economics University named after Vadym Hetman, Kyiv, Ukraine

V.Korenyev,, Zaporizhzhia National University, Zaporizhzhia, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

I.Vasylchuk,, State University of Economics and Technology, Kryvyi Rih, Ukraine

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2021, (2): 193 - 197


Improvement of regression economic-mathematical models taking into account the influence of residual error as a random variable.

Methods of economic-mathematical modeling, regression analysis are used. The real conditional law of distribution of residual error as a complete characteristic of a random variable is applied.

A scientific and practical approach to economic and mathematical modeling based on the study on residual error, to improve the construction of regression equations.

For the first time, the application of residual error analysis as a random variable has been proposed in order to construct its conditional differential distribution function, which allows improving the quality of economic-mathematical modeling in the form of regression equations. The use of the proposed method of taking into account the residual error allows eliminating the negative impact of the violation of the conditions of the properties of the residual error in the implementation of economic and mathematical modeling using regression equations.

Practical value.
The analysis of the obtained results of economic-mathematical modeling of economic activity of Inhulets Mining and Processing Plant on significant statistical material with the use of the developed algorithm of residual error research confirmed the effectiveness of the proposed approach. It is recommended to include the developed algorithm taking into account the properties of the residual error in the practice of managing the financial activities of mining enterprises.

mining enterprises, regression, model, residual error, scedasticity, financial activity


1. Chornous, G.O. (2014). Proactive management of socio-economic systems based on data mining. Methodology and models: monograph. Kyiv: VPC Kyiv University.

2. Sheremet, A.D. (2014). Comprehensive analysis of indicators of sustainable development of the enterprise. Economic analysis: theory and practice, (45), 2-10.

3. Savitskaya, G.V. (2014). Analysis of efficiency and risks of entrepreneurial activity: methodological aspects: monograph. Moscow: Research Center INFRA-M.

4. Vitlinskyi, V.V. (2017). Methodological principles of risk modeling in the system of economic security. Modeliuvannia ta informatsiini systemy v ekonomitsi, (94), 14-27.

5. Kyzym, M. (2015). Cluster format for arranging and implementing industrial policy. Acta Innovations, (17), 30-40.

6. Ponomarenko, V.S., & Gontareva, I.V. (2015). Methodology of comprehensive assessment of the effectiveness of enterprise development: monograph. Kharkiv: KhNEU named after S.Kuznets.

7. Trided, O.M., & Dzebko, I.P. (2015). Implementation of strategic management accounting as a tool to increase the competitiveness of the company International collection of scientific works, 1(19), 376-382.

8. Udalykh, O.O. (2016). Budgeting as a method of economic management of the enterprise. Financial research, (1), 96-100.

9. Leontieva, L.S., & Orlova, L.N. (2016). The use of the principles of matrix modeling for a comprehensive assessment of the effectiveness of institutional change in entrepreneurship Mir. Modernization. Innovation. Development, 7(1), 97-101.

10. Levchenko, N.M., & Nosenko, D.K. (2009). Analysis of the efficiency of innovative production of enterprises. Bulletin of Khmelnytskyi National University, 2(1), 138-142.

11. Burkova, L.A. (2014). Theoretical foundations for assessing the effectiveness of enterprises and ways to improve it. Innovative economy, (4), 145-153.

12. Mishchuk, Ie., Nusinov, V., Kashubina, Y., Polishchuk,I., & Pasichnyk, N. (2021). Security of strategic economic interests of mining and metallurgical enterprises in post-industrial conditions as factor of their investment attractiveness. Academy of Strategic Management Journal, 20(1), 1-9.

13. Nusinov, V.Ya., Mishchuk, Ie.V., & Izmaylov, Ya. (2019). Development of the stereometric method to the analysis of economic categories and processes and its application in security and taxation. Baltic Journal of Economic Studies, 5(4), 160-170.

14. Maliarets, L.M., Misiura, Ye.Yu., & Koibichuk, V.V. (2016). Mathematical methods and models in the management of economic processes: monograph. Kharkiv: KhNEU im. S.Kuznetsya.

15. Carlberg, K. (2017). Regression analysis in Microsoft Excel. Moscow: Williams.

16. State Statistics Service of Ukraine (n.d.). Retrieved from

17. SMIDA Cabinet of information services (n.d.). Retrieved from

18. Voskoboinikov, Yu.E. (2011). Regression data analysis in the Mathcad package (+ CD): monograph. St. Petersburg: Publishing house Lan.



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ISSN (print) 2071-2227,
ISSN (online) 2223-2362.
Journal was registered by Ministry of Justice of Ukraine.
Registration number КВ No.17742-6592PR dated April 27, 2011.


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