#### Name

Orlov Alexander Ivanovich

#### Scholastic degree

•

•

•

#### Academic rank

professor

#### Honorary rank

â€”

#### Organization, job position

Bauman Moscow State Technical University

#### Web site url

â€”

## Articles count: 123

Controlling of statistical methods to ensure product
quality is the special case of controlling
organizational and economic methods of
management. Today, controlling in the practice of
management of Russian companies is understood
as "the system of information-analytical and
methodological support to achieve their goals." The
controller is developing a decision-making rules,
the head takes decisions on the basis of these rules.
We proved the concept of "controlling of
methods". Innovation in management is based, in
particular, on the use of new adequate
organizational-economic (as well as economicmathematical
and statistical) methods. Controlling
in this area - is the development and application
procedures of compliance management used and
newly developed (implemented) organizationaleconomic
methods for the task. Thus, the
methodology for controlling is of great practical
value in any field in which the actions (operations)
must be carried out in accordance with certain rules
(regulations, standards, guidelines), as in any such
area in which we need to use development and
application procedures of compliance management
used and the newly established (implemented)
rules for solution of tasks assigned to the
organization. In this article, we select a area of
controlling as controlling quality, and we discuss
its main issues. This is about controlling of
organizational-economic methods to ensure
product quality, especially about the statistical
methods based on probability theory and
mathematical statistics. We consider the analysis
and synthesis of plans of statistical quality control,
optimization options plans of statistical control,
truncated plans. Are discussed the differences
control plans provider and the consumer, the
allocation of units formless (liquid, gas) products,
the selection of a random sample of the statistical
quality control of products, lower estimate of the
required sample size. It is established, that is not
always necessary quality control. Is given the
theory of the basic paradox of statistical quality
control. We discuss the development of statistical
methods for quality control in our country. Is given
the classification of statistical methods of quality management

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)

Sociology is one of the most important social
sciences. Mathematical and primarily statistical
methods are effective intellectual tools of
sociologists. Let us analyze the work of the author of
this article on the development of statistical methods
to meet the challenges of sociology. Then we give
the review of development of statistical methods in
Russian sociology for 45 years (1970-2015). The
basic scientific events of these years, first of all, were
formation of applied statistics and its basis - statistics
of the non-numerical data (in sociology of 70-90% of
variables have non-numerical nature). Over the last
30 years, the Russian sociology has been growing
rapidly in all quantitative parameters. Clearly, the
depth of investigation gives the use of advanced
scientific apparatus - methodology and methods of
data collection and analysis, mathematical models. In
our view, a fundamental breakthrough was made in
our country in the 1970s. It was then in the arsenal of
Russian sociologists appeared measurement theory
and fuzzy sets, mathematical methods of
classification and multidimensional scaling,
nonparametric statistics and statistics of non-numeric
data. In subsequent decades it has been a natural
development of scientific apparatus. The same
mathematical and statistical methods and models can
be successfully applied in various fields of science
and practice. Statistical methods and models are very
effective in sociological, socio-economic,
managerial, technical and feasibility studies,
medicine, history, in almost any industry and
application areas of knowledge. Within this field, the
main event of the last thirty five years - is becoming
a scientific and practical discipline "Applied
Statistics", dedicated to the development and
application of statistical methods and models. An
analysis of the dynamics of applied statistics leads to
the conclusion that in the XXI century the statistics
of non-numerical data is becoming a central area of
applied statistics, as it contains the most common
approaches and results

This article gives a review of mathematical methods of construction and using of classifications. The main approaches to solving the problems of cluster analysis and grouping are discussed. We have also proposed global and local natural classification criteria. The methods of discriminant analysis
(diagnosis, pattern recognition with the teacher) are discussed in connection with the construction of generalized indicators (ratings)

When developing management solutions with the
aim of joint consideration and comparison of
various factors, partial removal of uncertainty is
widely used ratings. In the theory of decisionmaking
in almost the same sense, we use the terms
"composite index" or "integrated indicator". The
article is devoted to the mathematical theory of
ratings as tools for studying socio-economic
systems. We considered, primarily, linear ratings
which is a linear function from a single (private)
indicators (factors, criteria), constructed using the
coefficients of importance (weightiness,
importance). The study discusses the factors
affecting the magnitude of the ratings. Three groups
of causes affect the value of a line ranking: the ways
of measurement of individual indicators, the choice
of the set of indicators; the values of the coefficients
of importance. We considered binary ratings when
the rating takes two values. To compare the
proposed rankings we use a new indicator of the
quality of diagnostics and prognostic power.
Significantly, in many managerial situations,
significant differences between objects are identified
using any rating. According to the fundamental
results of stability theory, the same source data
should be processed in several ways. Matching
findings, obtained using multiple methods, likely
reflect the properties of reality. The difference is the
result of a subjective selection method. When using
the results of the comparison of objects according to
several indicators (criteria ratings), including in
dynamics, very useful is the selection of the Pareto
set. We discuss the examples of the application of
the decision theory, expert evaluations and rankings
when developing complex technical systems

The article introduces the basic concepts of control theory. It has also noted the multicriteriality of real control problems. After reviewing the basic concepts of the theory of modeling we have analyzed postwar history and current status of mathematical modeling of control processes. We have also discussed the modeling methodology. As an example of a real model of the management process we have considered a model of allocation of time between the acquisition of knowledge and development of skills

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

Statistical methods are widely used in domestic
feasibility studies. However, for most managers,
economists and engineers, they are exotic. This is
because 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 awarded 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. In econometrics we select three
types of scientific and applied activities:
development and study of methods of applied
statistics, taking into account the specifics of
economic data; development and study of
econometric models, in accordance with the specific
needs of economic science and practice; the use of
econometric methods for statistical analysis of
specific economic data. This article describes these
three types of scientific and applied activities. We
discuss the specificity of economic data. We show
the importance of economic non-numeric values. We
discuss the statistics of interval data - scientific
direction at the joint of metrology and statistics. We
give the representation of the econometric models.
Problems of application of econometric methods are
considered as an example of inflation. We discuss
the statistics and econometrics as the field of
scientific and practical activities. We have examined
econometric methods in practical and training
activities

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

In accordance with the new paradigm of mathematical statistics the statistics of objects of nonnumerical nature (statistics of nonnumerical objects, non-numerical data statistics, non-numeric statistics) is one of the four main areas of mathematical statistics. Statistics of objects of nonnumerical nature consists of a central core - statistics in spaces of arbitrary nature - and statistical theories of analysis of specific types of non-numeric data. To identify possibilities of application of statistics of objects of nonnumerical nature it is useful to explore the multiformity of objects of non-numeric nature. This is the subject of this article. We have considered the results of measurements at scales other than absolute; binary relations; dichotomous (binary) data; sets. We have also analyzed the objects of non-numerical nature as statistical data, and their importance in the formation of statistical or mathematical model of a real phenomenon, as a result of data analysis