Janusz Soboń | Natalia Burkina | Kostiantyn Sapun | Ruslana Seleznova
pages: 62-69;
JEL classification: A1, C1, C5, C6, C8;
Keywords: multifactor regression, forecasting revenue, correlational and regression analysis;
Abstract: An important role in ensuring effective forms of management and increasing competitiveness is
played by the process of forecasting the activity of the enterprise. This work analyzed the
performance of a food industry enterprise, for which a wide range of statistical methods were
applied such as methods of cluster, correlational and regression analysis, statistical tests of
Fisher, Student, Farrar-Glauber, Durbin-Watson, Goldfeld-Quandt, μ-criterion, multifactor
regression, trend, auto-regression models, and models of seasonal fluctuations, which provided
a view of the economic properties of the enterprise profit process, in particular the
auto-regression component of revenue dependence on its value last year, seasonal quarterly
dependence on sales and marketing costs, product price, etc. The detected patterns will allow us
to take into account these features for forecasting future revenues and for adjusting the
enterprise’s decision-making system taking into account seasonal features and results of the
previous year.