scholarly journals Correlation and regression analysis of the investment attractiveness of the petroleum refining industry

Upravlenie ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 27-38
Author(s):  
M. M. Gayfullina ◽  
G. Z. Nizamova
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Petroleum Refining ◽  
Pair Correlation ◽  
Refining Industry ◽  
Oil Refining ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Analysis Package ◽  
Petroleum Refining Industry

The article presents the results of the analysis of the investment attractiveness of the petroleum refining industry using correlation and regression methods. It has been suggested to evaluate the level of investment attractiveness of the petroleum refining industry through capital productivity. A system of indicators affecting the investment attractiveness of the petroleum refining has been formed in the context of resource and production, financial, economic and social groups of factors. This methodology of correlation and regression analysis for modeling factors affecting investment attractiveness has been presented. The methodology includes the construction of a pair correlation, the selection of factors, the construction of a generalised correlation matrix using the “Correlation” tool in the “Data Analysis” package Microsoft Excel, the regression analysis based on the finally selected factors, the construction of the regression equation, the justification of the obtained dependence using the “Regression” tool in the “Data Analysis” package MS Excel.According to the results of calculations for the type of economic activity “Production of coke and petroleum products” in the Russian Federation in dynamics for 2012 –2019, a strong correlation has been revealed between the output-capital ratio and such factors as the oil refining depth, profit from sales and labor productivity.The results of the study can be used to identify significant factors affecting the investment attractiveness of the petroleum refining industry in order to further optimise them.

scholarly journals CORRELATION AND REGRESSION ANALYSIS OF THE AUTOMOTIVE GASOLINE MARKET

2021 ◽  
Vol 3 (37) ◽  
pp. 35-44
Author(s):  
G.Z. Nizamova ◽  
◽  
M.M. Gaifullina ◽  
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Oil Production ◽  
Regression Equation ◽  
Raw Material ◽  
Oil Refining ◽  
Gasoline Market ◽  
Factors Affecting ◽  
Motor Gasoline ◽  
Correlation And Regression Analysis

Purpose of the study: to identify the factors affecting the volume of production of motor gasoline. Research methods: analysis and synthesis, systematic approach, as well as methods of correlation and regression analysis. Results of the research: A methodological approach to the use of tools for correlation and regression analysis of the gasoline market is proposed, which includes the following stages: 1) formation of a data array; 2) carrying out correlation analysis, building a correlation matrix, selecting factors into the model using the Correlation tool in the Data Analysis package of MS Excel; 3) conducting a regression analysis, constructing a regression equation, substantiating the obtained dependence using the "Regression" tool in the "Data Analysis" MS Excel package, calculating the elasticity coefficients. It is proposed to use the volume of production of motor gasoline as effective in carrying out the correlation-regression analysis and constructing mathematical models. Among the dependent variables and factors affecting the volume of production of motor gasoline, it is proposed to use variables that characterize four groups of factors: resource (raw material) limitations (the volume of oil production and refining), production capabilities of the industry (through the depth of oil refining and the yield of light oil products that characterize production capacity and set of installations in the industry), price attractiveness of the market (prices of producers and consumers of motor gasoline, world oil prices), export attractiveness (volume and value of exports). Multivariate economic and statistical models of the dependence of the volume of production of motor gasoline on a number of factors have been developed. Based on the results of calculations, a strong correlation was revealed between the volume of production of motor gasoline and the values of primary oil refining, oil production, and export of motor gasoline. The predicted values are located as close as possible to the residual values, which indicates that the resulting regression equation has a high degree of accuracy. Research prospects: the research results can be used to identify significant factors in the development of the motor gasoline market in the Russian Federation.

Studying the factors of regional insurance market development using the correlation and regression analysis

2020 ◽  
Vol 26 (7) ◽  
pp. 1610-1630
Author(s):  
E.L. Prokop'eva
Keyword(s):  
Regression Analysis ◽  
Federal District ◽  
Insurance Market ◽  
Market Development ◽  
Insurance Markets ◽  
Regression Equations ◽  
Factors Affecting ◽  
Correlation And Regression Analysis ◽  
Country Level ◽  
Inverse Effect

Subject. The article investigates and quantifies factors of insurance markets functioning in Russian regions, and reveals possibilities to manage them. Objectives. The purpose of the study is to substantiate regional factors that determine the specifics of regional insurance market development; to quantify them to increase the efficiency of regional insurance. Methods. The study draws on statistical methods, functional analysis, algorithm development, correlation and regression analysis. Results. I calculated coefficients of pair and multiple correlation with the indicators of insurance markets in the context of the subjects of the Russian Federation, and composed regression equations. Based on the analysis, I determined the algorithm for inverse effect of the insurance market on the economic, social, fiscal and environmental performance of the region, offered appropriate measures aimed at developing the economic potential of the region and its social sphere. Conclusions. The paper considers the case of the Republic of Khakassia, one of depressed subjects in the Siberian Federal District. The developed models can be used for other regions of Russia, given the geographical and economic features of development. The findings may help generate regional strategies for socio-economic development at the country level. The scientific contribution and the novelty of the work consist of systematizing and quantifying the factors affecting the insurance mechanisms of regional markets, and assessing the inverse effect of insurance mechanisms on integrated development of the region.

scholarly journals Research on Hazardous Waste Removal Management: Identification of the Hazardous Characteristics of Fluid Catalytic Cracking Spent Catalysts

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2289
Author(s):  
Haihui Fu ◽  
Yan Chen ◽  
Tingting Liu ◽  
Xuemei Zhu ◽  
Yufei Yang ◽  
...  
Keyword(s):  
Surface Water ◽  
Hazardous Waste ◽  
Environmental Quality ◽  
Catalytic Cracking ◽  
Petroleum Refining ◽  
Fluid Catalytic Cracking ◽  
Refining Industry ◽  
Spent Catalyst ◽  
Spent Catalysts ◽  
Petroleum Refining Industry

Fluid catalytic cracking (FCC) spent catalysts are the most common catalysts produced by the petroleum refining industry in China. The National Hazardous Waste List (2016 edition) lists FCC spent catalysts as hazardous waste, but this listing is very controversial in the petroleum refining industry. This study collects samples of waste catalysts from seven domestic catalytic cracking units without antimony-based passivation agents and identifies their hazardous characteristics. FCC spent catalysts do not have the characteristics of flammability, corrosiveness, reactivity, or infectivity. Based on our analysis of the components and production process of the FCC spent catalysts, we focused on the hazardous characteristic of toxicity. Our results show that the leaching toxicity of the heavy metal pollutants nickel, copper, lead, and zinc in the FCC spent catalyst samples did not exceed the hazardous waste identification standards. Assuming that the standards for antimony and vanadium leachate are 100 times higher than that of the surface water and groundwater environmental quality standards, the leaching concentration of antimony and vanadium in the FCC spent catalyst of the G set of installations exceeds the standard, which may affect the environmental quality of surface water or groundwater. The quantities of toxic substances in all spent FCC catalysts, except those from G2, does not exceed the standard. The acute toxicity of FCC spent catalysts in all installations does not exceed the standard. Therefore, we exclude “waste catalysts from catalytic cracking units without antimony-based passivating agent passivation nickel agent” from the “National Hazardous Waste List.”

The Petroleum Refining Industry of Russia: Today and tomorrow

1993 ◽  
Vol 29 (9) ◽  
pp. 413-416
Author(s):  
�. F. Kaminskii ◽  
I. T. Kozlov ◽  
S. G. Ashitko
Keyword(s):  
Petroleum Refining ◽  
Refining Industry ◽  
Petroleum Refining Industry

Methodology for substantiating the indicators of economic entities for solving the problems of determining their reliability and stability in the organizational network

Innotrans ◽  
2021 ◽  
pp. 14-20
Author(s):  
Vasiliy M. Say ◽  
◽  
Dariya Yu. Gorelova ◽  
Keyword(s):  
Regression Analysis ◽  
Economic Activity ◽  
Production Capacity ◽  
Control Points ◽  
Microsoft Excel ◽  
High Performing ◽  
Organizational Network ◽  
Correlation And Regression Analysis ◽  
Analysis Package ◽  
The Stability

The article proposes a method for selecting parameters based on correlation and regression analysis in order to further include significant variables in the equation of stability of an enterprise of an organizational network. The sample consists of ten businesses and ten hypothetical control points. Three subsystems are accepted for consideration: technical and economic (nine indicators), organizational and legal (seven indicators) and human resources (seven indicators of economic activity of a legal entity). The proposed methodology allows us to justify significant indicators for each of the three subsystems for determining the stability of network elements (enterprises), depending on the overall trend of production capacity: a successfully developing enterprise; a high-performing enterprise; a low-performing one. This method allows us to predict the possible volume of deliveries from enterprises - elements of the network. To achieve this goal, it is proposed to use the apparatus of multivariate analysis, in particular, correlation and regression analysis, which allows us to determine the presence of links and their closeness between factors, as well as the degree of influence on the studied value. The calculations were performed using the “Correlation” and “Regression” tools included in the “Data Analysis” package of the Microsoft Excel program.

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