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


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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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