The document discusses five types of mathematical models: iconic, analogical, symbolic, deterministic, stochastic, static, and dynamic. Each model is defined with examples highlighting their characteristics and applications, such as iconic models representing physical replicas and deterministic models producing consistent outputs. The content is geared towards helping students prepare for university exams in computer science and related subjects.

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2. BUSINESS INTELLIGENCE
Types Of Mathematical Models
Mrs. Megha Sharma
M.Sc. Computer Science. B.Ed.
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3. Mathematical
Models
A mathematical model is a
description of a system using
mathematical concepts
and language. The process of
developing a mathematical model is
termed mathematical modeling
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4. Types Of Mathematical Models
ICONIC
STOCHASTIC
DETERMINISTIC
ANALGOICAL
SYMBOLICAL
DYNAMIC
STATIC
CHARACTERSTICS
TEMPORAL
DIMENSION
PROBABILISTIC
NATURE
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5. ICONIC
Physical replicas are referred to as Iconic Models
Iconic model is material representation of real system,
whose behaviour is follows for the purpose of
analysis.
E.g. Miniature model of airplane, car or bridge
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6. ANALOGICAL
 Analogical model are small physical system that have similar
characteristics and work line an original object or system.
 They are not replica of problem situation. Actual system is
complex and might not allow direct handling or manipulation
 E.g. Organization charts, showing structure authority and
responsibility relationship.
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7. SYMBOLICAL
Symbolic model is an abstract representation of a
real system.
It is intended to describe the behaviour of the
system through a series of symbolic variables,
numerical parameters and mathematical
relationships.
E.g. Graphs, Chart table.

8. DETERMINISTIC
All data inputs are supposed to be known a prior with
certainty.
In this model everything is predefined, and results are
uncertain. Beneficial for a variety of management
problems.
a deterministic system is a system in which no
randomness is involved in the development of future
states of the system.
A deterministic model will thus always produce the same
output from a given starting condition or initial state
It can help to reach the right business based on an ideal
customer profile.
E.g. Calculation to determine selling price if cost price is
200 and profit is 20%
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9. STOCHASTIC
A stochastic model is a tool for estimating probability
distributions of potential outcomes by allowing for random
variation in one or more inputs over time.
In this model some input information represents random
events and is therefore characterized by a probability
distribution.
In these models some inputs to the model are not known
with certainly.
Often used for strategic decision making involving an
organization relationship to its environment.
E.g. Predictive models, waiting line models.
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10. STATIC
A static model describes the static structure of the
system being modeled, which is considered less likely to
change than the functions of the system.
Static model consider a given system and the related
decision-making processes within one single temporal
stage.
E.g. Regression Models.
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11. DYNAMIC
The dynamic model represents the time–dependent
aspects of a system. It is concerned with the temporal
changes in the states of the objects in a system.
With a dynamic model processes are continuously
adjusted based on an analysis of context specific failures
and ensure that each step contributes to positive result.
E.g. An order interacts with inventory to determine
product availability.
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12. Thanks For Watching.
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