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In the article, the author discusses the importance of factor analysis methods, including the method of the main components, when studying multivariable information in the process of statistical analysis, with the aim of further modeling and predicting random processes. Key problems are described, when solving which they often turn to the method of the main components, as well as its algorithm, taking into account the fact that those interested in this article are familiar with the essence of statistical entimes. There is given a graphical representation of the author’s software, which reads the file specified by the user with a sample of data, made in the form of a table, which automatically prepares them for further analysis and search of the main components. The program functionality allows: to automatically calculate the mathematical expectation, variance of a multidimensional random variable; a covariance matrix for describing the shape of a random variable from which it is possible to obtain its dimensions by automatically finding eigenvectors and aigenpars; reduce the size of the sample; recover data for further hypothesis building and modeling. The algorithm of the principal component method is presented schematically.