### Abstract

The relevance of the problem stated in the article is due to the fact that there is a great variety of statistical methods now. The survey of the peculiarities of statistical methods indicates the wide possibility of applying the methods and stages of the correlation and regression analysis when building a model. The significance of the specification stage when building the regression model is determined, its theoretical basis and essence are described. One of the important aspects of the specification stage is the selection of the most significant variables (factors). The purpose of the article is to create and prove the model of integration of general and special economic disciplines with mathematics, to suggest the algorithm of the selection of factors at the specification stage of building the regression model in the framework of the application of integrative intersubject connections. The leading approach to the study of this issue is the method of formation of professional competence of future economists through the application of mathematical methods and models, knowledge and skills, which, in turn, provides the development of basic economic knowledge and skills. In the article we developed the method of solving the problem of application of mathematical statistics methods in building the econometric models in the framework of integration of intersubject connections, and we suggested the algorithm of selection of variables for building the effective regression model, which contributes to the conscious selection of the factors in the model and ensures the accuracy of real trends of the model and the model assessments, the obtainment of adequate forecast results.

### License

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

INT ELECT J MATH ED, 2016, Volume 11, Issue 8, 3021-3036

Publication date: 07 Sep 2016

Article Views: 3232

Article Downloads: 8459

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