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ТЕОРИЯ И ПРАКТИКА СОВРЕМЕННОЙ НАУКИ
VI международная научно-практическая конференция | МЦНС «НАУКА И ПРОСВЕЩЕНИЕ»
UDC 33
USE OF MULTI-DIMENSIONAL STATISTICAL
METHODOLOGY IN EVALUATION OF
COMPETITIVENESS OF ENTERPRISE PRODUCTS
Sakieva Ozoda Batirovna
Senior Lecturer,
Termez State University
The main findings and research
Nowadays, a number of methods for assessing the competitiveness of the enterprise have been devel-
oped and practically used. In many cases, these methods use the same type of data that characterizes a par-
ticular aspect of an enterprise’s operations. Analysis based on such indicators does not provide a complete
description of the enterprise's market position. In this case, it is necessary to use a method that describes the
system of indicators that reflect the main aspects of the enterprise.
One solution to this problem is to use multidimensional analysis methods of comparison in economic re-
search. The main problem in performing this type of calculation is the diversity of the set of factors that being
analyzed. A taxonomic indicator can be used to homogenize indicators with a large number of different units of
measurement. It represents an artificial size that characterizes the competitiveness of an enterprise using dif-
ferent symbols.
While using the method of taxonomic analysis to assess the competitiveness of the enterprise on the
basis of the coefficients of competitiveness of the enterprise, a matrix of observations is made to assess the
level of quality of the previously evaluated enterprise or product. Structured matrices are not homogeneous,
they represent different properties of the product quality level. In addition, their units of measurement are also
different, making it difficult to perform some arithmetic calculations, so it is necessary to standardize these
units. To do this, the arithmetic mean 𝑥
к
̅̅̅for the exponent k is calculated based on the formula 𝑥
𝑘
̅̅̅ =
1
𝜔
∑
𝑥
𝑖𝑘
𝜔
𝑖=1
(1). Then k is the standard deviation of the indicator
Abstract: The article provides theoretical data from the methods of multidimensional statistical analysis for the
application of taxonomic and hierarchical analysis methods in assessing the competitiveness of the enterprise
product.
Key words: multidimensional analysis methods, matrix of observations, taxonomic analysis, arithmetic calcu-
lations, deviation.
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