Population and sample. Numerical characteristics of position and dispersion

All professional life G.V. Sukhodolsky passed within the walls of the Leningrad-St. Petersburg University: from the time he graduated from the department of psychology of the Faculty of Philosophy of Leningrad State University in 1962 and until recently Gennady Vladimirovich Sukhodolsky was born on March 3, 1934 in Leningrad into a family of native St. Petersburg residents. Wandering with the parental family, evacuated from St. Petersburg to difficult years blockade, led to the fact that G.V. Sukhodolsky belatedly began studying at high school, after graduating from school he served in the army. G. V. Sukhodolsky became a student at Leningrad State University, being a completely mature person with a rich life experience. Perhaps it is precisely the adult attitude towards professional activity from its very beginning led to further extraordinary successes.
The entire professional life of G. V. Sukhodolsky passed within the walls of the Leningrad-St. Petersburg University: from the time he graduated from the psychology department of the Faculty of Philosophy of Leningrad State University in 1962 and until last days life. He went from a laboratory assistant at the first laboratory of industrial psychology in the USSR, where he worked under the direct supervision of the founder of engineering psychology, Academician B.F. Lomov, to the head of the department of ergonomics and engineering psychology.
Professor G.V. Sukhodolsky became one of Russia's leading experts in the field of labor psychology, engineering psychology and mathematical psychology, had extensive experience in scientific, applied and pedagogical activity. The monographs and textbooks he wrote allow him to rightfully be called one of the founders of the Leningrad and then St. Petersburg school of engineering psychology.
G. V. Sukhodolsky did a lot of pedagogical work: he developed original general courses"Application mathematical methods in psychology”, “Mathematical psychology”, “Engineering psychology”, “Experimental psychology”, “Higher mathematics, measurements in psychology”, as well as special courses “Structural-algorithmic analysis and synthesis of activities”, “Psychological service at the enterprise”, “Engineering -psychological examination of road traffic accidents.”
Participated in the organization and conduct of all all-Union conferences on engineering psychology from 1964 to 1990. He was vice-president of the International Conference on Ergonomics (L., 1993), organizer and permanent leader of the scientific and practical seminar on psychological services of enterprises (Sevastopol, 1988–1992).
From 1974 to 1996, G. V. Sukhodolsky was the chairman of the methodological commission of the Faculty of Psychology, whose work contributed to the improvement of the training of psychologists. For two official terms, he headed the specialized Academic Council for the defense of dissertations in engineering psychology and labor psychology.
Under the leadership of G.V. Sukhodolsky, dozens of theses, 15 candidate and 1 doctoral dissertations.
G. V. Sukhodolsky, having acquired rich experience in private research various types professional activities (tracking systems, navigation, heavy industry, timber rafting, nuclear energy, etc.), developed the concept of activity as an open system that assimilates and generates mental and non-mental products, based on a systemic synthesis of humanitarian and natural science approaches in psychology. He proved the need for multiple theoretical concepts of complex psychological (and other) objects and developed a methodology for multi-portraiting such objects in empirical research and mutual mathematical-psychological interpretation in psychological theory and practice.
Practical application of the concept developed by G. V. Sukhodolsky in the field of professional training: creation of models of variable stochastic algorithms and algorithmic structures of activity, including algorithms of dangerous (emergency) actions that need to be taught to improve labor safety; development of methods for studying the actions of operational personnel at consoles and posts for various purposes, including in the control room of nuclear power plants; development of a method for optimal layout and ergonomic examination of panels and consoles; Creation psychological methods examination of road traffic accidents. Long years

(Document)

n1.doc

Preface to the second edition

Preface to the first edition

Chapter 1. QUANTITATIVE CHARACTERISTICS OF RANDOM EVENTS

1.1. EVENT AND MEASURES OF POSSIBILITY OF ITS APPEARANCE

1.1.1. Concept of an event

1.1.2. Random and non-random events

1.1.3. Frequency, Frequency and Probability

1.1.4. Statistical definition of probability

1.1.5. Geometric definition of probability

1.2. RANDOM EVENT SYSTEM

1.2.1. The concept of the event system

1.2.2. Co-occurrence of events

1.2.3. Dependency between events

1.2.4. Event Transformations

1.2.5. Event Quantification Levels

1.3. QUANTITATIVE CHARACTERISTICS OF THE SYSTEM OF CLASSIFIED EVENTS

1.3.1. Event Probability Distributions

1.3.2. Ranking of events in the system by probabilities

1.3.3. Measures of association between classified events

1.3.4. Sequences of events

1.4. QUANTITATIVE CHARACTERISTICS OF THE SYSTEM OF ORDERED EVENTS

1.4.1. Ranking of events by magnitude

1.4.2. Probability distribution of a ranked system of ordered events

1.4.3. Quantitative characteristics of the probability distribution of a system of ordered events

1.4.4. Measures of rank correlation

Chapter 2. QUANTITATIVE CHARACTERISTICS OF A RANDOM VARIABLE

2.1. RANDOM VARIABLE AND ITS DISTRIBUTION

2.1.1. Random value

2.1.2. Probability distribution of random variable values

2.1.3. Basic properties of distributions

2.2. NUMERIC CHARACTERISTICS OF DISTRIBUTION

2.2.1. Measures of position

2.2.3. Measures of skewness and kurtosis

2.3. DETERMINATION OF NUMERICAL CHARACTERISTICS FROM EXPERIMENTAL DATA

2.3.1. Starting points

2.3.2. Compute measures of position, dispersion, skewness, and kurtosis from ungrouped data

2.3.3. Grouping data and obtaining empirical distributions

2.3.4. Calculation of measures of position, dispersion, skewness and kurtosis from an empirical distribution

2.4. TYPES OF RANDOM VARIABLE DISTRIBUTION LAWS

2.4.1. General provisions

2.4.2. Normal Law

2.4.3. Normalization of distributions

2.4.4. Some other laws of distribution important for psychology

Chapter 3. QUANTITATIVE CHARACTERISTICS OF A TWO-DIMENSIONAL SYSTEM OF RANDOM VARIABLES

3.1. DISTRIBUTIONS IN A SYSTEM OF TWO RANDOM VARIABLES

3.1.1. System of two random variables

3.1.2. Joint distribution of two random variables

3.1.3. Particular unconditional and conditional empirical distributions and the relationship of random variables in a two-dimensional system

3.2. POSITION, DISPERSION AND COMMUNICATION CHARACTERISTICS

3.2.1. Numerical characteristics of position and dispersion

3.2.2. Simple Regressions

3.2.4. Measures of correlation

3.2.5. Combined characteristics of position, dispersion and communication

3.3. DETERMINATION OF QUANTITATIVE CHARACTERISTICS OF A TWO-DIMENSIONAL SYSTEM OF RANDOM VARIABLES ACCORDING TO EXPERIMENTAL DATA

3.3.1. Simple regression approximation

3.3.2. Determination of numerical characteristics with a small amount of experimental data

3.3.3. Complete calculation of the quantitative characteristics of a two-dimensional system

3.3.4. Calculation of the total characteristics of a two-dimensional system

Chapter 4. QUANTITATIVE CHARACTERISTICS OF A MULTIDIMENSIONAL SYSTEM OF RANDOM VARIABLES

4.1. MULTIDIMENSIONAL SYSTEMS OF RANDOM VARIABLES AND THEIR CHARACTERISTICS

4.1.1. The concept of a multidimensional system

4.1.2. Varieties of multidimensional systems

4.1.3. Distributions in a multidimensional system

4.1.4. Numerical characteristics in a multidimensional system

4.2. NON-RANDOM FUNCTIONS FROM RANDOM ARGUMENTS

4.2.1. Numerical characteristics of the sum and product of random variables

4.2.2. Laws of distribution of a linear function of random arguments

4.2.3. Multiple Linear Regressions

4.3. DETERMINATION OF NUMERICAL CHARACTERISTICS OF A MULTIDIMENSIONAL SYSTEM OF RANDOM VARIABLES ACCORDING TO EXPERIMENTAL DATA

4.3.1. Estimation of probabilities of multivariate distribution

4.3.2. Definition of multiple regressions and related numerical characteristics

4.4. RANDOM FEATURES

4.4.1. Properties and quantitative characteristics of random functions

4.4.2. Some classes of random functions important for psychology

4.4.3. Determining the characteristics of a random function from an experiment

Chapter 5. STATISTICAL TESTING OF HYPOTHESES

5.1. TASKS OF STATISTICAL HYPOTHESIS TESTING

5.1.1. Population and sample

5.1.2. Quantitative characteristics of the general population and sample

5.1.3. Errors in statistical estimates

5.1.5. Tasks of statistical testing of hypotheses in psychological research

5.2. STATISTICAL CRITERIA FOR ASSESSMENT AND TESTING OF HYPOTHESES

5.2.1. The concept of statistical criteria

5.2.2. X 2 -Pearson criterion

5.2.3. Basic parametric criteria

5.3. BASIC METHODS OF STATISTICAL HYPOTHESIS TESTING

5.3.1. Maximum likelihood method

5.3.2. Bayes method

5.3.3. Classical method for determining a parameter (function) with a given accuracy

5.3.4. Method for designing a representative sample using a population model

5.3.5. Method of sequential testing of statistical hypotheses

Chapter 6. FUNDAMENTALS OF VARIANCE ANALYSIS AND MATHEMATICAL PLANNING OF EXPERIMENTS

6.1. THE CONCEPT OF VARIANCE ANALYSIS

6.1.1. The essence of analysis of variance

6.1.2. Prerequisites for analysis of variance

6.1.3. Analysis of variance problems

6.1.4. Types of analysis of variance

6.2. ONE-FACTOR ANALYSIS OF VARIANCE

6.2.1. Calculation scheme for the same number of repeated tests

6.2.2. Calculation scheme for different numbers of repeated tests

6..3. TWO-FACTOR ANALYSIS OF VARIANCE

6.3.1. Calculation scheme in the absence of repeated tests

6.3.2. Calculation scheme in the presence of repeated tests

6.5. FUNDAMENTALS OF MATHEMATICAL PLANNING OF EXPERIMENTS

6.5.1. The concept of mathematical planning of an experiment

6.5.2. Construction of a complete orthogonal experimental design

6.5.3. Processing the results of a mathematically planned experiment

Chapter 7. BASICS OF FACTOR ANALYSIS

7.1. THE CONCEPT OF FACTOR ANALYSIS

7.1.1. The essence of factor analysis

7.1.2. Types of factor analysis methods

7.1.3. Tasks of factor analysis in psychology

7.2. UNIFACTOR ANALYSIS

7.3. MULTIFACTOR ANALYSIS

7.3.1. Geometric interpretation of correlation and factor matrices

7.3.2. Centroid factorization method

7.3.3. Simple latent structure and rotation

7.3.4. Example of multivariate analysis with orthogonal rotation

Appendix 1. USEFUL INFORMATION ABOUT MATRICES AND ACTIONS WITH THEM

Appendix 2. MATHEMATICAL AND STATISTICAL TABLES

Content

Preface to the second edition 3

Preface to the first edition 4

Chapter 1. QUANTITATIVE CHARACTERISTICS OF RANDOM EVENTS 7

1.1. EVENT AND MEASURES OF POSSIBILITY OF ITS APPEARANCE 7

1.1.1. Concept of event 7

1.1.2. Random and non-random events 8

1.1.3. Frequency, Frequency and Probability 8

1.1.4. Statistical definition of probability 11

1.1.5. Geometric definition of probability 12

1.2. RANDOM EVENT SYSTEM 14

1.2.1. Concept of the event system 14

1.2.2. Co-occurrence of events 14

1.2.3. Dependency between events 17

1.2.4. Event Transformations 17

1.2.5. Event Quantification Levels 27

1.3. QUANTITATIVE CHARACTERISTICS OF THE CLASSIFIED EVENT SYSTEM 29

1.3.1. Event Probability Distributions 29

1.3.2. Ranking of events in the system by probabilities 45

1.3.3. Measures of connection between classified events 49

1.3.4. Sequences of Events 54

1.4. QUANTITATIVE CHARACTERISTICS OF THE SYSTEM OF ORDERED EVENTS 61

1.4.1. Ranking of events by magnitude 61

1.4.2. Probability distribution of a ranked system of ordered events 63

1.4.3. Quantitative characteristics of the probability distribution of a system of ordered events 67

1.4.4. Rank correlation measures 73

Chapter 2. QUANTITATIVE CHARACTERISTICS OF A RANDOM VARIABLE 79

2.1. RANDOM VARIABLE AND ITS DISTRIBUTION 79

2.1.1. Random variable 79

2.1.2. Probability distribution of random variable values ​​80

2.1.3. Basic properties of distributions 85

2.2. NUMERICAL CHARACTERISTICS OF DISTRIBUTION 86

2.2.1. Regulation measures 86

2.2.3. Measures of skewness and kurtosis 93

2.3. DETERMINATION OF NUMERICAL CHARACTERISTICS FROM EXPERIMENTAL DATA 93

2.3.1. Starting points 94

2.3.2. Calculating measures of position, dispersion, skewness, and kurtosis from ungrouped data 94

2.3.3. Grouping data and obtaining empirical distributions 102

2.3.4. Calculating measures of position, dispersion, skewness and kurtosis from an empirical distribution 107

2.4. TYPES OF RANDOM VARIABLE DISTRIBUTION LAWS 119

2.4.1. General provisions 119

2.4.2. Normal Law 119

2.4.3. Normalization of distributions 130

2.4.4. Some other distribution laws important for psychology 136

Chapter 3. QUANTITATIVE CHARACTERISTICS OF A TWO-DIMENSIONAL SYSTEM OF RANDOM VARIABLES 144

3.1. DISTRIBUTIONS IN A SYSTEM OF TWO RANDOM VARIABLES 144

3.1.1. System of two random variables 144

3.1.2. Joint distribution of two random variables 147

3.1.3. Partial unconditional and conditional empirical distributions and the relationship of random variables in a two-dimensional system 152

3.2. POSITION, DISPERSION AND COMMUNICATION CHARACTERISTICS 155

3.2.1. Numerical characteristics of position and dispersion 155

3.2.2. Simple regressions 156

3.2.4. Measures of correlation 161

3.2.5. Combined characteristics of position, dispersion and communication 167

3.3. DETERMINATION OF QUANTITATIVE CHARACTERISTICS OF A TWO-DIMENSIONAL SYSTEM OF RANDOM VARIABLES ACCORDING TO EXPERIMENTAL DATA 169

3.3.1. Simple regression approximation 169

3.3.2. Determination of numerical characteristics with a small amount of experimental data 182

3.3.3. Complete calculation of the quantitative characteristics of a two-dimensional system 191

3.3.4. Calculation of the aggregate characteristics of a two-dimensional system 202

Chapter 4. QUANTITATIVE CHARACTERISTICS OF A MULTIDIMENSIONAL SYSTEM OF RANDOM VARIABLES 207

4.1. MULTIDIMENSIONAL SYSTEMS OF RANDOM VARIABLES AND THEIR CHARACTERISTICS 207

4.1.1. The concept of a multidimensional system 207

4.1.2. Varieties of multidimensional systems 208

4.1.3. Distributions in a multidimensional system 211

4.1.4. Numerical characteristics in a multidimensional system 214

4.2. NON-RANDOM FUNCTIONS FROM RANDOM ARGUMENTS 220

4.2.1. Numerical characteristics of the sum and product of random variables 220

4.2.2. Laws of distribution linear function from random arguments 221

4.2.3. Multiple Linear Regressions 224

4.3. DETERMINATION OF NUMERICAL CHARACTERISTICS OF A MULTIDIMENSIONAL SYSTEM OF RANDOM VARIABLES ACCORDING TO EXPERIMENTAL DATA 231

4.3.1. Estimating the probabilities of a multivariate distribution 231

4.3.2. Definition of multiple regressions and related numerical characteristics 235

4.4. RANDOM FEATURES 240

4.4.1. Properties and quantitative characteristics of random functions 240

4.4.2. Some classes of random functions important for psychology 246

4.4.3. Definition of characteristics random function from experiment 249

Chapter 5. STATISTICAL TESTING OF HYPOTHESES 254

5.1. TASKS OF STATISTICAL HYPOTHESIS TESTING 254

5.1.1. Population and sample 254

5.1.2. Quantitative characteristics of the general population and sample 261

5.1.3. Errors in statistical estimates 265

5.1.5. Tasks statistical testing hypotheses in psychological research 277

5.2. STATISTICAL CRITERIA FOR ASSESSMENT AND TESTING OF HYPOTHESES 278

5.2.1. The concept of statistical criteria 278

5.2.2. Pearson x2 test 281

5.2.3. Basic parametric criteria 293

5.3. BASIC METHODS OF STATISTICAL HYPOTHESIS TESTING 312

5.3.1. Maximum likelihood method 312

5.3.2. Bayes method 313

5.3.3. Classic method determining a parameter (function) with a given accuracy 316

5.3.4. Method for designing a representative sample using a population model 321

5.3.5. Method of sequential testing of statistical hypotheses 324

Chapter 6. FUNDAMENTALS OF VARIANCE ANALYSIS AND MATHEMATICAL PLANNING OF EXPERIMENTS 330

6.1. THE CONCEPT OF VARIANCE ANALYSIS 330

6.1.1. The essence of analysis of variance 330

6.1.2. Prerequisites for analysis of variance 332

6.1.3. Problems of analysis of variance 333

6.1.4. Types of analysis of variance 334

6.2. ONE-FACTOR ANALYSIS OF VARIANCE 334

6.2.1. Calculation scheme for the same number of repeated tests 334

6.2.2. Calculation scheme for different numbers of repeated tests 341

6..3. TWO-FACTOR ANALYSIS OF VARIANCE 343

6.3.1. Calculation scheme in the absence of repeated tests 343

6.3.2. Calculation scheme in the presence of repeated tests 348

6.5. FUNDAMENTALS OF MATHEMATICAL PLANNING OF EXPERIMENTS 362

6.5.1. The concept of mathematical planning of an experiment 362

6.5.2. Construction of a complete orthogonal experimental design 365

6.5.3. Processing the results of a mathematically planned experiment 370

Chapter 7. BASICS OF FACTOR ANALYSIS 375

7.1. THE CONCEPT OF FACTOR ANALYSIS 376

7.1.1. The essence of factor analysis 376

7.1.2. Types of factor analysis methods 381

7.1.3. Problems of factor analysis in psychology 384

7.2. UNIFACTOR ANALYSIS 384

7.3. MULTIFACTOR ANALYSIS 389

7.3.1. Geometric interpretation of correlation and factor matrices 389

7.3.2. Centroid factorization method 392

7.3.3. Simple latent structure and rotation 398

7.3.4. Example of multivariate analysis with orthogonal rotation 402

Appendix 1. USEFUL INFORMATION ABOUT MATRICES AND ACTIONS WITH THEM 416

Appendix 2. MATHEMATICAL AND STATISTICAL TABLES 425

Doctor psychological sciences, professor, honored worker high school RF.

Gennady Vladimirovich Sukhodolsky was born on March 3, 1934 in Leningrad into a family of native St. Petersburg residents. Wandering with his parental family, evacuated from St. Petersburg during the difficult years of the siege, led to the fact that G. V. Sukhodolsky belatedly began studying at secondary school, and after graduation he served in the army. G. V. Sukhodolsky became a student at Leningrad State University, being a completely mature person with rich life experience. Perhaps it was precisely the adult attitude towards professional activity from the very beginning that determined further extraordinary successes.

The entire professional life of G. V. Sukhodolsky passed within the walls of Leningrad - St. Petersburg University: from the time he graduated from the psychology department of the Faculty of Philosophy of Leningrad State University in 1962 until the last days of his life. He went from a laboratory assistant at the first laboratory of industrial psychology in the USSR, where he worked under the direct supervision of the founder of engineering psychology, Academician B.F. Lomov, to the head of the department of ergonomics and engineering psychology.

Professor G.V. Sukhodolsky became one of Russia's leading experts in the field of labor psychology, engineering psychology and mathematical psychology, and had extensive experience in scientific, applied and pedagogical activities. The monographs and textbooks he wrote allow him to rightfully be called one of the founders of the Leningrad and then St. Petersburg school of engineering psychology.

G. V. Sukhodolsky did a lot of pedagogical work: he developed original general courses “Application of mathematical methods in psychology”, “Mathematical psychology”, “Engineering psychology”, “Experimental psychology”, “Higher mathematics, measurements in psychology”, as well as special courses “Structural-algorithmic analysis and synthesis of activities”, “Psychological service at the enterprise”, “Engineering-psychological examination of road accidents”.

Participated in the organization and conduct of all all-Union conferences on engineering psychology from 1964 to 1990. He was vice-president of the International Conference on Ergonomics (L., 1993), organizer and permanent leader of the scientific and practical seminar on psychological services of enterprises (Sevastopol, 1988–1992).

From 1974 to 1996, G. V. Sukhodolsky was the chairman of the methodological commission of the Faculty of Psychology, whose work contributed to the improvement of the training of psychologists. For two official terms, he headed the specialized Academic Council for the defense of dissertations in engineering psychology and labor psychology. Under the leadership of G.V. Sukhodolsky, dozens of theses, 15 candidate's dissertations and one doctoral dissertation were defended.

G.V. Sukhodolsky, having acquired rich experience in private research of various types of professional activities (tracking systems, navigation, heavy industry, timber rafting, nuclear energy, etc.), developed the concept of activity as an open system that assimilates and generates mental and non-mental products, based on a systematic synthesis of humanitarian and natural science approaches in psychology. He proved the need for multiple theoretical concepts of complex psychological (and other) objects and developed a methodology for multi-portraiting such objects in empirical research and mutual mathematical-psychological interpretation in psychological theory and practice.

Practical application of the concept developed by G. V. Sukhodolsky in the field of professional training: creation of models of variable stochastic algorithms and algorithmic structures of activity, including algorithms of dangerous (emergency) actions that need to be taught to improve labor safety; development of methods for studying the actions of operational personnel at consoles and posts for various purposes, including in the control room of nuclear power plants; development of a method for optimal layout and ergonomic examination of panels and consoles; creation of psychological methods for the examination of road accidents. For many years, G.V. Sukhodolsky was a member of the expert council on the problem of human factors at the Ministry of Medium Engineering of the USSR.

G. V. Sukhodolsky studied problems of mathematical psychology for many years. The original methods he developed include: the method of multidimensional labeled stochastic matrices for treating complex objects; a method for visualizing finite-dimensional objects in the form of a profile in parallel coordinates; method of using multisets, generalization operations, mixed multiplication and division of multisets and data matrices; a new method for assessing the significance of correlation coefficients using the Snedecor-Fisher F-test and the significance of similarity - differences of correlation matrices using the Cochran G-test; method of normalizing distributions through the integral function.

The scientific developments of G. V. Sukhodolsky in the field of psychology of professional activity find their application and continuation in solving two important problems modern psychology labor and engineering psychology. The first task is to continue developing the theory of professional activity, methods of its description and analysis. This is a key direction in modern applied psychology, since the methodology, theory and tools for describing and analyzing activities are the basis for the development of all other areas of organizational psychology and solving applied problems: psychological support business process reengineering, performance management, job specification, organization group work etc. The work of G.V. Sukhodolsky in this direction is continued by S.A. Manichev (competency-based modeling of professional activity) and P.K. Vlasov (psychological aspects of organizational design). Second task - further development traditions of the activity approach in the context of modern cognitive ergonomics (design and evaluation of interfaces based on the study of human activity), as well as knowledge engineering. Usability, a scientific and applied discipline that studies the efficiency, productivity and ease of use of business tools, is gaining particular relevance and development prospects. The concept of analysis and synthesis of algorithmic structures of activity by G. V. Sukhodolsky has clear prospects for maintaining its importance in ensuring the ergonomic quality of interfaces. The multi-portrait methodology is used by V. N. Andreev (author of developments in interface optimization, now working in Vancouver, Canada) and A. V. Morozov (ergonomic assessment of interfaces).

IN last years life, despite a serious illness, Gennady Vladimirovich continued to be active scientific activity, wrote books, supervised graduate students. Gennady Vladimirovich was awarded prizes from the St. Petersburg state university for pedagogical excellence, for a series of monographs on the application of mathematical methods in psychology. In 1999 he was awarded the title “Honored Worker of Higher School Russian Federation", in 2003 - "Honorary Professor of St. Petersburg State University." The merits of G.V. Sukhodolsky have received wide recognition. He was elected a full member of the New York Academy of Sciences.

He is the author of more than 250 publications, including five monographs and four textbooks and teaching aids.

Main publications

• Fundamentals of mathematical statistics for psychologists. L., 1972 (2nd ed. - 1998).
• Structural-algorithmic analysis and synthesis of activities. L., 1976.
• Fundamentals of psychological theory of activity. L., 1988.
• Mathematical and psychological models of activity. St. Petersburg, 1994.
• Mathematical psychology. St. Petersburg, 1997.
• Introduction to the mathematical and psychological theory of activity. St. Petersburg, 1998.

Over the past 20 years, this book has not only not become outdated, but has acquired new relevance. Because over the past period, no new generalizing monographs on the psychology of activity have appeared, and Russian modernity and the prospect of development in the context of globalization require psychological study and design of new systems of human-technical activities from schooling to production management, international marketing and political life.

I am grateful to the URSS publishing house for the opportunity to reprint this book of mine and hope for interest in it from possible consumers of scientific knowledge.

G.V.Sukhodolsky,
Saint Petersburg
16.07.07

In Soviet psychology, the so-called “activity” approach developed, according to which the human psyche is formed and studied in activity and through activity. Based on the methodological principle of the unity of consciousness and activity, the conceptual apparatus and methods of psychology are created, theoretical and practical developments are carried out in psychological fields, as a result of which the activity approach is developed.

The main direction of this development is associated with the transition from explaining the human psyche by its activities to the psychological study and design of the activity itself as mediated by mental, as well as social and biological properties acting people, i.e. "human factor". The leading role here belongs to engineering psychology.

Engineering psychology is a branch of psychology that studies the relationship between man and technology in order to achieve high efficiency, quality and humanity of modern work, by designing it based on the psychological principles of designing equipment, working conditions, professional training and on the basis of engineering principles of taking into account the human factor in people. -technical systems.

The new technical reconstruction of production based on computerization and robotization, the creation of flexible production systems brings significant changes into established forms of professional activity. The main functions of a specialist in production are increasingly becoming the programming of machines, their management and control. Labor activity in production, management and management, and with computerization in school and educational activities are increasingly approaching in basic terms the activities of operators. In this regard, engineering psychology becomes a direct productive force and, being organically connected with psychological science as a whole, takes on all complex system relationships between psychology and other sciences and production.

Despite certain achievements, activity design remains one of the central problems engineering psychology and psychology in general, since experience has not yet been generalized psychological description activities and there are no reliable means of psychological assessment, optimization and design of both old and, especially, new types of activities. For this reason, the problem of activity is recognized as one of the most important problems for theoretical and practical development. In particular, it is necessary to create such a psychological theory labor activity person, which would equip practitioners with clear knowledge of the psychological mechanisms of this activity, the patterns of its development and methods of using the results of psychological research to solve practical problems; it is necessary to create a psychological theory joint activities, revealing its complex structure and dynamics, and ways to optimize it.

It is believed that the psychological theory of activity, which serves as a methodological basis for all psychological disciplines, is one of most important achievements Soviet psychology. However, in this theory there is vagueness and ambiguity in the interpretation of basic terms, the conceptual layer of the concept synthesized on the previous and additional apparatus is not generalized enough, poorly systematized and not brought together. Most general and special psychological concepts reflect the desire to limit the study of activity to narrow psychological patterns of mental functioning. At the same time, the actual professional, material, technical, technological and other non-psychological aspects of activities, from which the psyche of the “working person” turns out to be artificially separated, remain outside the study. Because of this desire in general psychology they try to reduce the subject of study to some kind of “mental”, “meaningful experiences” or “orienting activity”. Social psychology is primarily limited to interpersonal relationships and the phenomena based on them. In labor psychology, professiograms are largely reduced to psychograms, and psychograms are reduced to lists of professionally important properties or qualities that are not very specific to a particular activity. For the same reason, in engineering psychology, interactions between people and machines are reduced mainly to information interactions, which is also a certain result of cybernetic reductionism. In psychology, the study of activity is almost universally limited to its analysis, although this contradicts not only dialectics in general, but also specific psychological methodology and the practical use of results.

Thus, on the one hand, urgent state tasks have been set, in the solution of which psychology as a whole as a science should participate, and on the other hand, this participation is hampered by the shortcomings of psychological views on activity - shortcomings so significant that it is permissible to talk about the absence of a psychological theory of activity . Without at least the foundations (or beginnings) of such a theory, it is obviously impossible to solve the required problems correctly.

It seems that the above considerations sufficiently substantiate the relevance of the goals that we are pursuing and to which the content of the book, the logic and nature of the presentation are subordinated.

First of all, it is necessary to understand the existing psychological and other views on activity, to identify, generalize, clarify and systematize the conceptual apparatus of the psychology of activity. The first section of the book is devoted to this, in which “key” concepts are defined; the conceptual apparatus existing in the psychology of activity is identified and systematized; existing systemic concepts of activity are critically analyzed and evaluated.

The second section of the book sequentially sets out first the premises and theoretical scheme of the generalized psychological material, and then the conceptual structures reflecting the structure, need-value sphere, development and functioning, being and cognition of activities.

In conclusion, the results are summed up and some prospects for the development of activity psychology are outlined.

I consider it my duty to express gratitude to my teachers, staff and students for good relations, support and assistance.

Honored Worker of Higher School of the Russian Federation. Doctor of Psychological Sciences, Professor of the Department of Ergonomics and Engineering Psychology at St. Petersburg State University.

Range of scientific interests: general, engineering, mathematical psychology. Published 280 scientific works, including several monographs: “Fundamentals of mathematical statistics for psychologists” (1972, 1996); "Mathematical Psychology" (1997); "Introduction to the mathematical and psychological theory of activity" (1998); "Mathematics for Humanists" (2007).