Contents
COURSE DESCRIPTION
2
MISSION
2
VISION
2
NIÑO M. RODIL
2
COURSE REQUIREMENTS
INTENDED LEARNING OUTCOMES
2
3
PRE-TEST:
3
Problem Solving and Methodology
4
WHAT IS PROBLEM SOLVING?
4
PROBLEM SOLVING PROCESS
4
Rules in Problem Solving
6
Levels of Problem Solving
6
Techiniques of Problem Solving
6
Different Types of Methodologies
7
quantitaive measurement and models
8
WHAT IS QUANTITATIVE MEASUREMENT?
9
WHAT IS A MODEL?
10
MODELING METHODOLOGY
11
EXAMPLES OF MODELS
12
POST-TEST:
12
ANSWER KEY:
13
1
COURSE DESCRIPTION
ITEC95 – QUANTITATIVE METHODS (MODELLING
AND SIMULATION)
Republic of the Philippines
CAVITE STATE
UNIVERSITY
Bacoor City Campus
SHIV, Molino VI, City of Bacoor
To enable the students to the application of real-world
simulation and different uses of simulation models and
techniques. This course introduces the modeling and simulation
concepts. Topics discuss in the course includes system
analysis and classification, simulation models, continuous,
discrete and combined models such as heterogenous models.
It also covers the pseudorandom number generation testing,
queuing systems, Monte Carlo method and continuous
simulation.
Students should be able to use different simulation models and
techniques based on different situations and scenarios.
MISSION
Cavite State University shall provide
excellent, equitable and relevant
educational opportunities in the arts,
science and technology through
quality instruction and relevant
research and development activities.
It shall produce professional, skilled
and morally upright individuals for
global competitiveness.
PROGRAM OUTCOMES ADDRESSED BY
THE COURSE. AFTER COMPLETING THIS
COURSE, THE STUDENTS MUST BE
ABLE TO:
1. Attain the vision, mission, goals and objectives of
the university, campus and department;
2. Deliver a gender fair and gender sensitive
instruction to students aligned with University
goals and objectives.
3. Able to use appropriate mathematical tools for
decision making
4. Understand the implementation of mathematical
methods in IT solution to the problems
5. Understand the best practices and standards and
their applications
6. Analyzed complex problems, identify and define
the computing requirements appropriate to the
solution.
7. Integrate IT-based solutions into the user
environment effectively
VISION
The premier university in historic
Cavite recognized for excellence in
the development of globally
competitive and morally upright
individuals.
COURSE REQUIREMENTS
NIÑO M. RODIL
1. Homework/Activity
2. Long Examination
3. Midterm and Final Examination
Instructor I
nino.rodil@cvsu.edu.ph
‘
2
Republic of the Philippines
CAVITE STATE UNIVERSITY
Bacoor City Campus
SHIV, Molino VI, City of Bacoor
INTENDED LEARNING OUTCOMES
After the completion of the unit, students will be able to:
1. Identify key elements of problem solving
2. Demonstrate the knowledge of data sources including that internet based
3. Explain the difference between random and quota survey design
PRE-TEST:
Direction: Identify the terms describe by the following:
1. A systematic approach to defining problem and creating a vast number of possible
solutions without judging these solution.
2. Diagnose the situation so that your focus is on the problem, not just its symptoms.
3. Many alternative solutions to the problem should be generated before final
evaluation..
4. Skilled problem solvers use a series of considerations when selecting the best
alternative.
5. Leaders may be called upon to direct others to implement the solution, "sell" the
solution, or facilitate the implementation with the help of others.
6. Does not require much expertise and can even be solved by the managers at lower
levels of hierarchy.
7. These are not serious types but still have to be solves at the earliest as possible.
8. These are the ones to be resolved on priority, and need more attention and care.
Mostly, it will be handled by the top management.
9. Help to recognize the need for the problem solving as basis the weakness or
threats, they can also think in advanced about the probable problems that their
company might face in the near future and keep them under control or stop the
problem completely from occurring.
10. Seeks to explore a specific phenomena, not prove a prediction, according to
"Qualitative Research Methods:
11. More objective than qualitative methods. In this type of methodology, the
researcher crafts a hypothesis and then tests it through structured means.
12. Combine qualitative and quantitative research.
13. The lowest level of measurement.
14. The next level of measurement and contains slightly more specific information
than the nominal level.
15. A higher level of measurement
16. The highest level of measurement.
3
PROBLEM SOLVING AND METHODOLOGY
WHAT IS PROBLEM SOLVING?
●
A systematic approach to defining problem and creating a vast number of possible
solutions without judging these solution. A cognitive processing directed at
achieveing a goal where no solution method is obvious to the problem solver.
●
An instructional method or technique where by the teacher and students attempt
in a conscious planned and purposely effort to arrive of some explanation or
solution to some educationally significant difficulty for the purpose of finding a
solution.
●
Problem solving is the act of defining a problem; determining the cause of the
problem; identifying, prioritizing, and selecting alternatives for a solution.
PROBLEM SOLVING PROCESS
1. Define the problem
Diagnose the situation so that your focus is on the problem, not just its symptoms. Helpful
problem-solving techniques include using flowcharts to identify the expected steps of a
process and cause-and-effect diagrams to define and analyze root causes.
The sections below help explain key problem-solving steps. These steps support the
involvement of interested parties, the use of factual information, comparison of
expectations to reality, and a focus on root causes of a problem. You should begin by:
Reviewing and documenting how processes currently work (i.e., who does what, with what
information, using what tools, communicating with what organizations and individuals, in
what time frame, using what format).
Evaluating the possible impact of new tools and revised policies in the development of
your "what should be" model.
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Characteristics:
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Differentiate fact from opinion
Specify underlying causes
Consult each faction involved for information
State the problem specifically
Identify what standard or expectation is violated
Determine in which process the problem lies
Avoid trying to solve the problem without data
2. Generate Alternative Solutions
Postpone the selection of one solution until several problem-solving alternatives have
been proposed. Considering multiple alternatives can significantly enhance the value of
your ideal solution. Once you have decided on the "what should be" model, this target
standard becomes the basis for developing a road map for investigating alternatives.
Brainstorming and team problem-solving techniques are both useful tools in this stage of
problem solving.
Many alternative solutions to the problem should be generated before final evaluation. A
common mistake in problem solving is that alternatives are evaluated as they are
proposed, so the first acceptable solution is chosen, even if it’s not the best fit. If we focus
on trying to get the results we want, we miss the potential for learning something new
that will allow for real improvement in the problem-solving process.
Charancteristics
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Postpone evaluating alternatives initially
Include all involved individuals in the generating of alternatives
Specify alternatives consistent with organizational goals
Specify short- and long-term alternatives
Brainstorm on others' ideas
Seek alternatives that may solve the problem
3. Evaluate and select an alternative
Skilled problem solvers use a series of considerations when selecting the best alternative.
They consider the extent to which:
● A particular alternative will solve the problem without causing other unanticipated
problems.
● All the individuals involved will accept the alternative.
● Implementation of the alternative is likely.
● The alternative fits within the organizational constraints.
Charactertistics
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Evaluate alternatives relative to a target standard
Evaluate all alternatives without bias
Evaluate alternatives relative to established goals
Evaluate both proven and possible outcomes
State the selected alternative explicitly
4. Implement and follow up on the solution
Leaders may be called upon to direct others to implement the solution, "sell" the solution,
or facilitate the implementation with the help of others. Involving others in the
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implementation is an effective way to gain buy-in and support and minimize resistance to
subsequent changes.
Regardless of how the solution is rolled out, feedback channels should be built into the
implementation. This allows for continuous monitoring and testing of actual events
against expectations. Problem solving, and the techniques used to gain clarity, are most
effective if the solution remains in place and is updated to respond to future changes.
Characteristics
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Plan and implement a pilot test of the chosen alternative
Gather feedback from all affected parties
Seek acceptance or consensus by all those affected
Establish ongoing measures and monitoring
Evaluate long-term results based on final solution
RULES IN PROBLEM SOLVING
1. Solve problems that best suits to you. As you may be expert in a particular field or have
skills to reseolve problems of specific areas. Once this is done you can give solutions to
those problems quickly and efficiently.
2. Have a Mediator: Specially whn there are people problems in the organization, because
most of the times employees tend to take their immediate superiors for granted and
hence mediator can work well in such situations.
3. Train the managers on solving problems at their levels, they will not escalated to top
levels.
4. More communication, the more communication and interact with other experts on the
problem solving mechanism and strategies the more effective they turn out to be.
5. Some extreme cases, It is better to have redressed panel to solve more complicatd
issues.
LEVELS OF PROBLEM SOLVING
1. Simple
Does not require much expertise and can even be solved by the managers at lower
levels of hierarchy.
2. Moderate
These are not serious types but still have to be solves at the earliest as possible.
3. Complex
These are the ones to be resolved on priority, and need more attention and care.
Mostly, it will be handled by the top management.
Skills to use in Problem Solving
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Decision making
Motivation
Planning
Knowledge
Analytical skills
Experience
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Communication skills
Group skills
Judgement
Collecting information
TECHINIQUES OF PROBLEM SOLVING
1. Brainstorming
This usually takes place between experts, or group members between the people of
specific designations.
- It helpls motivating people to think of some ideas and creative ideas
- It develops teams
- It helps in problem solving
You can follow the following steps in brain storming:
a. Have a clear goals
As to what has to be concentrated on for problem solving, what is the problem, its
extent and urgency.
b. Suggest ideas and plans
All people will interact to contribute their share of ideas and suggestions.
c. Develop Options and Alternatives
Necessary same plan might work but you might have to re-work with different
plans.
d. Check the viability of each options
As to how effective they are, and how they help to solve the current problem.
e. Agree
All must agree to the final solution to the problem solving to be implemented.
f. Follow-up
To check the effectiveness and accuracy of the solutions, it necessary to follow
2. SWOT Analysis
S – Strengths (Capacity, Pricing, Branding, Location, Quality, Management, Innovation, etc)
W – Weakness (Process, Systems Working, Branding Status, Implementing the Projects,
etc)
O – Opportunities (Product Developments, Research and Development, New Contracts,
Increase in Market Share, Drawbacks of competitors)
T – Threats (Government, Politics, Competitor Variations, Change in Market Conditions,
etc)
SWOT Analysis can help to recognize the need for the problem solving as basis the
weakness or threats, they can also think in advanced about the probable problems that
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their company might face in the near future and keep them under control or stop the
problem completely from occurring.
Methodology
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A body of methods, rules and postulates employed by a discipline, a particular
procedures or set of procedures.
The analysis of principles or procedures of inquiry in a prticular field.
DIFFERENT TYPES OF METHODOLOGIES
1. Qualitative Research
Qualitative research seeks to explore a specific phenomena, not prove a
prediction, according to "Qualitative Research Methods: A Data Collector's Field
Guide," published by Family Health International. Often used in the social sciences
and education, qualitative methodologies use interviews, focus groups and
observations to collect data. Qualitative methods provide rich, contextual
explorations of the topic that are often personally or culturally meaningful.
2. Quantitative Methods
Quantitative research is more objective than qualitative methods. In this type of
methodology, the researcher crafts a hypothesis and then tests it through
structured means. Instead of exploring or describing a phenomena, quantitative
methods deal with facts and statistics. This type of research is often used in
science or medicine.
3. Mixed Methods
Mixed methods combine qualitative and quantitative research. This type of
methodology uses several different measures that include both contextual
understanding like interviews or observations along with facts or statistics. Using
mixed methods can help the researcher investigate a topic on multiple levels,
gaining different views and a comprehensive look at the subject. A mixed
methodology meshes more than one philosophical perspective, allowing for the
integration of different theories and ideas..
4. Methodologies and Design
Within each major methodology are various designs. These provide a framework
or philosophy for the study, and are different than the actual methods used. For
example, a case study design focuses on exploring and describing a specific
instance, person or group. A researcher may use observations, interviews or
self-reports from the subject to create a complete picture. This picture, or case,
provides a detailed example of a phenomenon that can then be generalized to a
similar population
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QUANTITAIVE MEASUREMENT AND MODELS
WHAT IS QUANTITATIVE MEASUREMENT?
Quantitative measurement is measurement of data that can be put into numbers. The
goal of quantitative measurement is to run statistical analysis, so data has to be in
numerical form. In Carrie’s case, her data is already quantitative; so is data like blood
pressure, height, or age.
Examples of a quantitative measurement
Examples of quantitative measurement methods are the following
1. Tracking logs
2. Questionnaires
3. Structured Observation
4. Knowledge and Achievement Tests
5. Physiological Health Status Measures.
Types of measurement
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Source: https://www.questionpro.com/blog/nominal-ordinal-interval-ratio/
You can see there are four different types of measurement scales (nominal, ordinal,
interval and ratio). Each of the four scales, respectively, typically provides more
information about the variables being measured than those preceding it.
1. Nominal
The nominal level of measurement is the lowest level of measurement. It contains
categories are mutually exclusive, which means means that anyone who falls into one
category cannot not fall into another category.
The data can be represented with words (like yes/no) or numbers that correspond to
words or a category (like 1 equaling yes and 0 equaling no). Even when the categories are
represented as numbers in our data, the number itself does not have an actual numerical
value.
The nominal level of measurement usually includes many demographic characteristics
like race, gender, or marital status.
2. Ordinal Level
The ordinal level of measurement is the next level of measurement and contains slightly
more specific information than the nominal level. This level has mutually exclusive
categories and a hierarchy or order.
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3. Interval Level
The interval level of measurement is a higher level of measurement. This level marks the
point where we are able. This level contains all of the characteristics of the previous levels
(mutually exclusive categories and order). What distinguishes it from the ordinal level is
that the interval level can be used to conduct mathematical computations with data (like
an average, for instance).
4. Ratio level data
Ratio level data is the highest level of measurement. It has mutually exclusive categories,
order, and you can perform mathematical operations on it.
The main difference between the interval and ratio levels is that the ratio level has an
absolute zero, meaning that a value of zero is both possible and meaningful. You might be
thinking, “Well, age has an absolute zero,” but someone who is not yet born does not have
an age, and the minute they’re born, they are not zero years old anymore.
How do you measure quantitative data?
Quantitative data makes measuring various parameters controllable due to the ease of
mathematical derivations they come with. Quantitative data is usually collected for
statistical analysis using surveys, polls or questionnaires sent across to a specific section
of a population.
What are measures in quantitative research?
Measures exist to numerically represent degrees of attributes. Quantitative research is
based on measurement and is conducted in a systematic, controlled manner. These
measures enable researchers to perform statistical tests, analyze differences between
groups, and determine the effectiveness of treatments.
WHAT IS A MODEL?
It is a theoretical description of a system or a process that helps to explain how it works.
WHAT IS A QUANTITATIVE MODEL?
It’s a theoretical and formal description of a system or a process that has been translated
into the language of mathematics. Eykhoff defined it beautifully as ‘a representation of
the essential aspects of an existing system (or a system to be constructed) which
presents knowledge of that system in usable form’. Focus on the phrase ‘usable form’, it’ll
come up later on.
MODELING METHODOLOGY
The modeling process is iterative, we may or may not get it right the first time. Also, some
models are in constant need of redefining their variables and assumptions, tweaking the
formulation, and ultimately comparing their results to reality. This is because in some
environments such as trading, systems in reality do change. The magnitude of change is
what determines whether a model should be updated or discarded.
MODEL TYPE SELECTION STAGE
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The type of a model can immediately tell you its structure and gives an overview of how it
works. Some types are more appropriate than others depending on what they will be
modeling.
EMPIRICAL
Approximate an undelying process that
generated a set of data
DETERMINISTIC
Fixed set of input creates the same
output
DISCRETE VARIABLES
Countabl and characterized by jumpls
and distinct values
STATIC
Captures a snapshot of process
LINEAR
If all operators within a mathematical
model are of linear nature then it is linear
THEORETICAL
Determine logical consequences from a
set of assumptions
STOCHASTIC
Similar inputs creates output from a
probability distribution
CONTINOUS VARIABLES
Smooth process with an infinite number
of potential values in any fixed interval
DYNAMIC
Captures the evolution of process and
descrbes it by the states
NON LINEAR
If all operators do not exhibit linearity
then they are non linear
DEFINITION & FORMULATION STAGE
Once we are able to define the model we are to build, we begin considering the type of
mathematical equations we are going to use. It is important to be very cautious while
selecting an equation as they can alter the behaviour of a model.
A mathematical model consists of the following constituents:
● Variables
● Equations
It is important to understand the types of variables that may exist in a mathematical
model, and they are:
DECISION VARIABLES
STATE VARIABLES
EXOGENOUS VARIABLES
RANDOM VARIABLES
Are the independent variable, the variable you want
to know
Used to describe the mathematical state of a
dynamical system.
Are the parameters/constants
Are variables where their value depends on the
outcome of random/stochastic system.
Typically, equations determine the relationships between variables. Here are other
equation usages a typical model may have:
GOVERNING EQUATIONS
DEFINING EQUATIONS
CONSTRAINTS
Describes how independent/unkown variables
change with respect to independent variable
Define new quantities in terms of base quantities
Set of predetermined conditions, such as initial
boundary and conditions
Mathematical equations establish the relationship between the variables which were
previously assumed in the model type selection stage.
Mathematical equations are built up of two things:
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Target expressions type: Are encompassing representations for your
mathematical functions. They take the model type and variables into consideration
Key mathematical functions & operations: which are the equations building blocks
takes relations into consideration
Operations allow us to combine the mathematical functions together to make compound
functions. These compound functions are ultimately described in the type our target
expression is.
EXAMPLES OF MODELS
There are many ready made models which were created using the target expressions and
mathematical functions. These models are so useful you can use them as your main
model for the system you are modeling or they can be used as sub-models within your
main model. They are bare and ready to be manipulated by your variables and/or data.
We will only brush through them. Here are some main examples:
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Linear models
Probabalistic/Stochastic models
Regression models
Multiple Regression
Line fitting
Curve fitting
Logistic Regression
Monte Carlo Simulations
Marcov Chain Models
POST-TEST:
Direction: Identify the terms describe by the following:
1. A systematic approach to defining problem and creating a vast number of possible
solutions without judging these solution.
2. Diagnose the situation so that your focus is on the problem, not just its symptoms.
3. Many alternative solutions to the problem should be generated before final
evaluation..
4. Skilled problem solvers use a series of considerations when selecting the best
alternative.
5. Leaders may be called upon to direct others to implement the solution, "sell" the
solution, or facilitate the implementation with the help of others.
6. Does not require much expertise and can even be solved by the managers at lower
levels of hierarchy.
7. These are not serious types but still have to be solves at the earliest as possible.
8. These are the ones to be resolved on priority, and need more attention and care.
Mostly, it will be handled by the top management.
9. Help to recognize the need for the problem solving as basis the weakness or
threats, they can also think in advanced about the probable problems that their
13
company might face in the near future and keep them under control or stop the
problem completely from occurring.
10. Seeks to explore a specific phenomena, not prove a prediction, according to
"Qualitative Research Methods:
11. More objective than qualitative methods. In this type of methodology, the
researcher crafts a hypothesis and then tests it through structured means.
12. Combine qualitative and quantitative research.
13. The lowest level of measurement.
14. The next level of measurement and contains slightly more specific information
than the nominal level.
15. A higher level of measurement
16. The highest level of measurement.
ANSWER KEY:
PRE-TEST
POST-TEST
IDENTIFICATION:
IDENTIFICATION:
1.
2.
3.
4.
Problem Solving
Define the problem
Generate Alternative Solutions
Evaluate and select an
alternative
5. Implement and follow up on the
solution
6. Simple
7. Moderate
8. Complex
9. SWOT Analysis
10. Qualitative Research
11. Quantitative Methods
12. Mixed Methods
13. Nominal
14. Ordinal Level
15. Interval Level
16. Ratio Level Data
1.
2.
3.
4.
5.
Problem Solving
Define the problem
Generate Alternative Solutions
Evaluate and select an alternative
Implement and follow up on the
solution
6. Simple
7. Moderate
8. Complex
9. SWOT Analysis
10. Qualitative Research
11. Quantitative Methods
12. Mixed Methods
13. Nominal
14. Ordinal Level
15. Interval Level
16. Ratio Level Data
14