In practice, economic analysis and assessment activity aggregate the results of research. As a rule, the size of a sample of partial indicators is limited due to the limited number of studied objects. When processing the results, an analyst may use a variety of statistical methods. Most commonly, the researchers use the method for calculating the arithmetic mean value of partial indicators. However, small amounts of sampling and a significant variance of values of partial indicators is essential to the sought-for indicator determination error based on averaging. Thus, the challenge is the choosing the aggregation method that provides the highest reliability and accuracy of the indicator. It is appropriate to mention here that when sample values are positive definite, more than one averaging method, not only the arithmetic one, may be applied. In his publication, the author submits a comparative analysis of the validity of the following values resulting from the statistical processing of economic indicators: arithmetic mean, geometric mean, harmonic mean, median and the root mean square values. The studies were executed on the basis of 16 model numerical experiments (samples). Each of the samples represented the superposition of a set of random uniformly distributed values, together with the true value. The paper shows that, in property evaluation practice, the use of RMS values of performance indicators is more preferable in comparison with other methods of statistical processing.
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