Scientific Journal of KubSAU

In 1970 in the journal publications of "Forbes" and "Business week" the term of "startup" appeared, which later became popular in the scientific and business literature. Startups are the organizations, which create a new product or service under conditions of high uncertainty. In the last 25-30 years, due to Russia's transition from a planned economy to the mixed, many researchers and practitioners in the field of management, economics and entrepreneurship are concerned of some questions of small business, including production. It is particularly acute problem of deaths of Russian small businesses: only three out of a hundred small businesses manage to survive for more than 3 years. In addition, one of the main reasons, why we have such statistics, is management deficiencies and administrative errors, which are studied in this article. We are primarily interested in small manufacturing plants and problems of development in the early stages of the life cycle. In the literature, it has been given just little attention. A small production company is a company associated with the production organization or incorporation of the product / technology in the production process. We regard the small production companies at an early stage of development, working in the field of mechanical engineering, instrumentation, energy, telecommunications, robotics, materials production. In this work, we analyze the first foreign and then domestic research on small business, discuss the problems of management of small industrial enterprises in the early stages of the life cycle (based on the results of our questionnaire studies) and as an example, consider the story of a startup - All-Union Center of statistical methods and Informatics of Central Board of the All-Union economic society (now - Institute of high statistical technologies and econometrics of Bauman Moscow State Technical University)

In the training courses on the theory of probability and mathematical statistics there are various parametric families of distributions of numerical random variables considered. Namely, we have been studying the families of normal distributions, log-normal distributions, exponential distributions, gamma distributions, Weibull-Gnedenko distributions, etc. All of them depend on one, two or three parameters. Therefore, for a complete description of the distribution it is sufficient to know or estimate one, two or three numbers. Parametric theory of mathematical statistics is widely developed, where it is assumed that the distribution of observations belong to one or another parametric family of distributions. This tradition comes from Karl Pearson, who in the early twentieth century proposed the use of four parametric family of distributions. The above families of distributions - are the subsets of a four-parametric family of Pearson. Unfortunately, parametric families exist only in the minds of the authors of textbooks on probability theory and mathematical statistics. In real life, they are not. Therefore, modern applied statistics and econometrics mainly use non-parametric methods, in which the distribution of observations can have arbitrary form. First, on an example of a normal distribution, we are discussing the impossibility of practical use of parametric families of distributions to describe specific statistical data. We give the results of research of metrologists and estimation of convergence in limit theorems. Then we discuss how the parametric methods can use for reject outlying observations. It is very unstable the significance levels for a fixed rejection rule and the parameter of the rejection rules for a fixed level of significance. Consequently, the rejection of the classic rules of mathematical statistics is not sciencebased

In various applications, it is necessary to analyze several expert orderings, i.e. clustered rankings objects of examination. These areas include technical studies, ecology, management, economics, sociology, forecasting, etc. The objects can be some samples of products, technologies, mathematical models, projects, job applicants and others. In the construction of the final opinion of the commission of experts, it is important to find clustered ranking that averages responses of experts. This article describes a number of methods for clustered rankings averaging, among which there is the method of Kemeny median calculation, based on the use of Kemeny distance. This article focuses on the computing side of the final ranking among the expert opinions problem by means of median Kemeny calculation. There are currently no exact algorithms for finding the set of all Kemeny medians for a given number of permutations (rankings without connections), only exhaustive search. However, there are various approaches to search for a part or all medians, which are analyzed in this study. Zhikharev's heuristic algorithms serve as a good tool to study the set of all Kemeny medians: identifying any connections in mutual locations of the medians in relation to the aggregated expert opinions set (a variety of expert answers permutations). Litvak offers one precise and one heuristic approaches to calculate the median among all possible sets of solutions. This article introduces the necessary concepts, analyzes the advantages of median Kemeny among other possible searches of expert orderings. It identifies the comparative strengths and weaknesses of examined computational ways

Statistical methods are widely used in domestic feasibility studies. However, for most managers, economists and engineers, they are exotic. This is due to the fact that modern statistical methods are not taught in the universities. We discuss the situation, focusing on the statistical methods for economic and feasibility studies, ie, econometrics. In the world of science, econometrics has a rightful place. There are scientific journals in econometrics, Nobel Prizes in Economics are given to series of researches in econometrics. The situation in the field of scientific and practical work and especially the teaching of econometrics in Russia is disadvantaged. Often, individual particular constructions replace econometrics in general, such as those related to regression analysis. The article is devoted to econometrics as an academic discipline. Our course begins with a discussion of the structure of modern econometrics, the connections between applied statistics and econometric methods. We consider sample researches (analysis of surveys results), the elements of econometrics numbers, and methods of testing of statistical hypothesis about homogeneity. We have given the concepts of regression analysis, econometric classification methods, modern measurement theory. The important places are occupied by the statistics of non-numerical data (including fuzzy sets and their links with random sets) and the statistics of interval data. The problem of the stability of statistical procedures with respect to the tolerances of input data and model prerequisites is discussed. The representations of the econometric methods of expert research and quality control, analysis and forecasting of time series, econometrics of forecasting and risks are given

In 2011 – 2015, the scientific community was represented by a new paradigm of mathematical methods of research in the field of organizational and economic modeling, econometrics and statistics. There was a talk about a new paradigm of applied statistics, mathematical statistics, mathematical methods of economics, the analysis of statistical and expert data in problems of economics and management. We consider it necessary to develop organizational and economic support for solving specific application area, such as the space industry, start with a new paradigm of mathematical methods. The same requirements apply to the teaching of the respective disciplines. In the development of curricula and working programs, we must be based on a new paradigm of mathematical methods of research. In this study, we present the basic information about a new paradigm of mathematical methods of research. We start with a brief formulation of a new paradigm. The presentation in this article focuses primarily on the scientific field of "Mathematical and instrumental methods of economy", including organizational and economic and economic-mathematical modeling, econometrics and statistics, and decision theory, systems analysis, cybernetics, operations research. We discuss the basic concepts. We talk about the development of a new paradigm. We carry out a detailed comparison of the old and the new paradigms of mathematical methods of research. We give information about the educational literature, prepared in accordance with the new paradigm of mathematical methods of researches

One of the "points of growth" of applied statistics is methods of reducing the dimension of statistical data. They are increasingly used in the analysis of data in specific applied research, such as sociology. We investigate the most promising methods to reduce the dimensionality. The principal components are one of the most commonly used methods to reduce the dimensionality. For visual analysis of data are often used the projections of original vectors on the plane of the first two principal components. Usually the data structure is clearly visible, highlighted compact clusters of objects and separately allocated vectors. The principal components are one method of factor analysis. The new idea of factor analysis in comparison with the method of principal components is that, based on loads, the factors breaks up into groups. In one group of factors, new factor is combined with a similar impact on the elements of the new basis. Then each group is recommended to leave one representative. Sometimes, instead of the choice of representative by calculation, a new factor that is central to the group in question. Reduced dimension occurs during the transition to the system factors, which are representatives of groups. Other factors are discarded. On the use of distance (proximity measures, indicators of differences) between features and extensive class are based methods of multidimensional scaling. The basic idea of this class of methods is to present each object as point of the geometric space (usually of dimension 1, 2, or 3) whose coordinates are the values of the hidden (latent) factors which combine to adequately describe the object. As an example of the application of probabilistic and statistical modeling and the results of statistics of non-numeric data, we justify the consistency of estimators of the dimension of the data in multidimensional scaling, which are proposed previously by Kruskal from heuristic considerations. We have considered a number of consistent estimations of dimension of models (in regression analysis and in theory of classification). We also give some information about the algorithms for reduce the dimensionality in the automated system-cognitive analysis

We are developing a new organizational-economic theory - solidary information economy, based on the views of Aristotle. The name of this theory has changed over time. Initially, we used the term "nonformal information economy of the future", and then began to use the term "solidary information economy." In connection with Biocosmology and neo-Aristotelism preferred is an adequate term "functionalist organic information economy". This article summarizes the first phase of work on the solidary information economy. We have analyzed the array of publications. The main problems are discussed, the solution of which is devoted to research related to the considered basic organizational and economic theory. The founder of the economic theory is Aristotle. We discuss Aristotle's positions, on which the economic theory is based, in particular, solidary information economy. We prove that the market economy has remained in the XIX century and the mainstream in modern economic science - justification of insolvency of a market economy and the need to move to a planned system of economic management. We examine the impact of ICT on economic activity. We develop the approaches to decision-making in the solidary information economy. On the basis of modern decision theory (especially expert procedures) and informationcommunication technologies people can get rid of chrematistics and will understand the term of "economy" according to Aristotle

We have considered the formation of the Russian scientific school in the field of econometrics, obtained its obtained scientific results, the possibilities of their use in solving problems of the economy, the organization of production and controlling of industrial companies and organizations, as well as in teaching. As econometrics we consider a scientific and an academic discipline devoted to the development and application of statistical methods to study economic phenomena and processes, in short, statistical methods in economics. Therefore, we can say that a lot of domestic books and articles, in particular, the works by the author of this publication from the beginning of the 70s, are the parts of econometrics. However, in this article we consider only the works, in the titles of which we can see the word of "econometrics". In our country the term "econometrics" has become popular since the mid 90s. However, many publications and training courses are still developed in the western outdated paradigm. They do not conform to the new paradigm of mathematical methods of economics, the new paradigm of applied statistics and mathematical statistics, mathematical methods of research. Russian science school in the field of econometrics operates within the scientific school in the field of probability theory and mathematical statistics based by A.N. Kolmogorov. Russian science school is developed in accordance with the new paradigm of mathematical methods. It is necessary to examine the main results of Russian scientific schools in the field of econometrics. We present the information on the institutional design of national scientific schools in econometrics, in particular, on the activities of the Institute of High Technologies statistics and econometrics

The founder of the economic theory is Aristotle. The so-called "market economy" is a perversion of Aristotle's views. We have to eliminate distortions. What can replace the "market economy"? We are developing a new organizational-economic theory - solidary information economy, based on the views of Aristotle. The name of this theory has changed over time. Initially, we used the term "nonformal information economy of the future", and then began to use the term "solidary information economy." In connection with Biocosmology and neo-Aristotelism preferred is an adequate term "functionalist organic information economy". This article describes the main provisions of solidary information economy, intended to replace the market economy as a management tool. The main problems are discussed, the solution of which is devoted to research related to the considered basic organizational and economic theory. We discuss Aristotle's positions, on which the economic theory is based, in particular, solidary information economy. We prove that the market economy has remained in the XIX century and the mainstream in modern economic science - justification of insolvency of a market economy and the need to move to a planned system of economic management. We examine the impact of ICT on economic activity. We develop the approaches to decision-making in the solidary information economy. On the basis of modern decision theory (especially expert procedures) and informationcommunication technologies people can get rid of chrematistics and will understand the term of "economy" according to Aristotle

Adequate and effective assessment of the efficiency, effectiveness and the quality of scientific activities of specific scientists and research teams is crucial for any information society and a society based on knowledge. The solution to this problem is the subject of scientometrics and its purpose. The current stage of development scientometrics differs greatly from his previous appearance in the open as well as paid on-line access to huge amount of detailed data on a large number of indicators on individual authors and on scientific organizations and universities. The world has well-known bibliographic databases: Web of Science, Scopus, Astrophysics Data System, PubMed, MathSciNet, zbMATH, Chemical Abstracts, Springer, Agris, or GeoRef. In Russia, it is primarily the Russian scientific citing index (RSCI). RSCI is a national information-analytical system, accumulating more than 9 million publications of Russian scientists, as well as the information about citation of these publications from more than 6,000 Russian journals. There is too much information; it is so-called "Big data". But the problem is how to make sense of these large data, more precisely, to identify the meaning of scientometric indicators) and thus to convert them into great information ("great information"), and then apply this information to achieve the objective of scientometrics, i.e. to transform it into a lot of knowledge ("great knowledge") about the specific scientists and research teams. The solution to this problem is creating a "Scientific smart metering system" based on the use of the automated system-cognitive analysis and its software tools – an intellectual system called "Eidos". The article provides a numerical example of the creation and application of Scientometric intelligent measurement system based on a small amount of real scientific data that are publicly available using free on-line access to the RSCI