7.What is the difference between functional and dysfunctional consequences of conflict?
8.Compile a glossary of terms, supported the sense-conveying components of lecture meaning orgraph.
9.Transform a part of lecture orgraph from tabular to graphic form.
Lecture 14. ELEMENTS OF DECISION-MAKING THEORY
There are rules to choose decisions but there are no rules to choose these rules.
Enon “Laws of scientific work”
Problem of decision-making arises when formalization mechanism cannot be determined immediately. In cases like that it is necessary to determine problem situation of an object, expose factors that cause that situation, detect possible tools (mathematical objects), to describe situation and relate the goal and the means. There are three stages in the decision-making process.
The lecture plan of meaning orgraph is given in table 14.
Таble 14
The lecture plan of meaning orgraph
Elements of decision-making theory |
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Notion of decision-making |
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The first stage of decision-making |
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Problem comprehension owing to |
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Increase of empirical knowledge, accumulation of |
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experimental data, detection of cause-effect |
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relationship |
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Problem statement |
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Types of problems – possibility, crisis, routine |
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Problem types |
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End of Table 14
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Analysis problem – diagnostic, dispersive, |
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combinatorial, structural, functional |
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Problem of synthesis, development, stabilization |
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Problem ranking – criteria determination |
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The second stage of decision-making (alternatives |
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generation) |
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Choice of alternatives: based on past experience, |
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experiment, analysis |
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Choice of alternatives taking into account the state of |
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external environment |
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Probabilistic assessment of the state of external |
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environment, results assessment of implementing |
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alternatives within external environment |
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Expertise of alternatives |
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Routine problems solved with expertise |
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Decision - making |
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Decision rules according to revenue data |
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Maximax, maximin, minimax, Gurvitz |
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Decision rules implementing numerical values of |
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probability outcomes |
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Maximum probability, mathematical |
expectation, |
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revenue maximization (minimization of losses) |
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Decision implementation |
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The third stage of decision-making: assessment of effect |
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expected |
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Total |
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Bibliography list for students` autonomous work [26, 33].
Checklist questions
1.What is the sense of diagnostic analysis?
2.What is the sense of combinatorial analysis? Give the example.
3.What is the sense of structure functional analysis? Give the example.
4.Give the definition of experiment. What is the purpose of experiments?
5.Give the example empirical model.
6.Give the definition of analysis and synthesis.
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7.Give the definition of criteria.
8.Give the definition of expertise.
9.Give the example of routine problems solved with expertise.
10.Give the example of an alternative.
11.Give the definition of probability.
12.What is the sense of decision-making without implementing numerical values of probability outcomes?
13.What is the difference between maximax and maximin rules?
14.What is the sense of decision-making when implementing numerical values of probability outcomes?
15.What is the sense of mathematical expectation?
16.Compile a glossary of terms, supported the sense-conveying components of lecture meaning orgraph.
Lecture 15. ELEMENTS OF EXPERIMENT THEORY
Experiment is the teacher you need to take after.
B. Pascal
Experiment is the technique to obtain new knowledge under controllable and manageable conditions, first of all about cause-effect relationship between phenomena and processes. The notion ‘experiment” means the process of creation conditions of multiple repetition of this or that phenomena of an object or subject.
The logic of experiment as a scientific method was developed by J. S. Mill in the 19 century. It assumes the double rule of distinction in an agreement: if within the experiment after the set of events если A,B,D comes an event а, but after В and D does not come а, then А is the cause of а. The first of the two sets of events is considered as experimental, and the second one as control. This classic plan of making experiments was supplemented with multiple-factor experiment later on, and the Mill`s
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double rule was provided with statistic analysis procedure (dispersive, factorial etc.).
Thus, an experiment is perceptional-objective scientific activity done with the view of accumulation of experience, reproduction of object of knowledge, verification of hypothesis etc.. An experiment is carried out in natural environment or under simulated natural conditions. The principle methodological technique to study an object is the technique of
‘black” box when input variables xl..., xм are called factors, |
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The lecture plan of meaning orgraph is given in table 15. |
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The lecture plan of meaning orgraph |
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Таble 15 |
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Structure of sense-conveying components of the section |
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Aim of experiment |
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Terminology of dispersive analysis in experiment |
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Factor, reaction |
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Experimental conditions, types of an experiment |
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Passive experiment |
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Active experiment |
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Calculating experiment according to a model |
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Error of experiment result |
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Result of experiment - quantity |
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Classification of quantities according to number of |
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values |
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Notion of “algebra” of result processing |
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Ordinary Least Squares, Lagrangian representation |
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Result of experiment - event |
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Classification of events |
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Authentic, impossible, random (possible) event, joint |
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and disjoint event, dependent and independent event, |
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event of equal possibilities, opposite event |
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Classic definition of probability |
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Probability of ordinary events |
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Probability as a ratio of quantity of favourable |
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outcomes to their total quantity (rearrangements, |
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allocations, combinations) |
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Probability as a ratio of measure sets |
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End of Table 15
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Probability of complex events |
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Probability of complex event represented in the |
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form of multiplication of elementary events |
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Probability of complex event represented in the |
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form of orgraph (outcome array; total outcome |
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probability) |
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Geometrical determination of probability |
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Statistical determination of probability |
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Total |
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Checklist questions
1.Give the definition of experiment and what is the sense and the aim of an experiment?
2.What is the fundamental difference between passive and active experiments?
3.What is the sense of computing experiment?
4.What is the result of an experiment?
5.What is the fundamental difference between OLS and Lagrangian representation?
6.Give the definition of event. Give the example.
7.Give the example of dependent and independent events.
8.Give the example of ordinary event.
9.Give the example of complex event.
10.Give the definition of orgraph.
11.How does probability of complex event correlate with probability of independent ordinary event?
12.Give the example of ordinary and complex events distribution.
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