APPLICATION OF MULTIFACTOR STATISTICAL STUDIES IN ECONOMICS

Abstract

This article examines multifactor statistical studies as an effective tool for quantitative analysis, forecasting, and optimization of economic processes in enterprises of various sizes and fields of activity. The main focus is on the full factorial experiment (FFE) as a method for systematically evaluating the influence of multiple independent factors on dependent economic indicators, as well as for identifying possible interactions among them.

Within the framework of the study, methods for factor coding, calculation of regression coefficients, and testing the statistical significance and adequacy of the constructed models using appropriate criteria are discussed.

Through a practical example conducted in a small and medium-sized enterprise, the influence of three key factors—product price, advertising costs, and number of employees—on profit is demonstrated. In the example, specific regression coefficients are calculated in euros, which allows for direct economic interpretation of the results and their use in managerial decision-making.

The article emphasizes the importance of the multifactor statistical approach for improving resource efficiency, forecasting financial results, and optimizing strategic business decisions. The obtained results and models can be applied to practical planning, evaluation of investment strategies, and decision-making aimed at increasing the firm’s competitiveness in the market.