Correlation-regression analysis of factors affecting inventories of production enterprise

Abstract

The article highlights the feasibility of correlation-regression analysis and inventory modeling at a manufacturing enterprise using applications. Inventory modeling will help to optimize them and further increase the profitability of the enterprise. The use of applications will speed up and simplify the modeling process and strengthen the analytical component. Among the modern variety of applications for statistical and econometric analysis, it is important to choose an effective software product, simple and easy to use, which does not require significant costs. It is offered to use a free, but no less high-quality R-Studio product, which is easy to use and fast to calculate. On the example of application of the free application program R-Studio the correlation-regression analysis is carried out and the regression model of stocks at the production enterprise of PJSC "Novokramatorsk Machine-Building Plant" is constructed. The influence of internal factors on the company's stocks, such as: net income from sales of products (goods, works, services), net financial result: profit, accounts payable for goods (works, services) and external: GDP and the dollar. According to the simulation results, the greatest influence among internal factors has the net income from sales of products (goods, works, services). Among external factors, GDP is the most influential. The constructed model is adequate, as evidenced by a significant indicator of the Fisher criterion and the coefficient of determination. 90% of the stocks of the studied enterprise depend on the selected factors. The construction of a matrix of correlation coefficients and correlation analysis confirmed the close relationship between the selected factors and their impact on stocks as a result. The example of PJSC "Novokramatorsk Machine-Building Plant" demonstrates the practical usefulness of inventory modeling using computer programs.