Quantitative Business Analysis
Course Introduction
By
Aziza Munir
Course Description
• Focus on Data handling and presentation
• Analyse the need and importance of collecting
data in business and methods to interpret them
• Describe, estimates, probability and forecasting
environment on the basis of given information
• Presentation of numeric data and theoretical
interpretations for information and business
application
Course Objectives
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Data as center of generating information
Data gathering techniques
Mathematical and statistical interpretations
Research techniques
Generating useful information
Course Methodology
• Part 1
Focus on estimates, probability, discrete and
continuous, probability distribution, and decision
analysis
Forecasting on the basis of time series
• Part 2
Importance of research in business
Techniques, functions and steps
Data interpretation and presentation, statistically
Lecture 1
Introduction
By
Aziza Munir
Learning Objectives
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Need and developing model
Model types
Flow chart of transformational process
Model solution and report generation
Quantitative methods in practice
summary
Why Model?
To successfully apply quantitative analysis to
decision making, the analyst must work with
manager or user of the results. When both the
quantitative analyst and the manager agree that
the problem has been adequately structured,
model can be developed and work can begin.
Model development
• Models are presentations of real objects or
situations and can be presented in various
forms.
Eg. Scale model of an airplane is a
representation of real airplane. Similarly child
toy truck is a model of real truck. These are
physical replicas of objects
• Iconic models
Model development and types
• Second classification includes models that are
physical in form but do not have same physical
appearance, as object being modeled. Such
are known as Analog Models
Eg: Speedometer of an automobile, position of
needle on dial, thermometer mentioning
temperature
Model development and Types
• Third classification states, representation of a
problem by system of symbols and
mathematical relationing.
• Mathemetical Modeling
Eg: Total profit from sales of a product can be
determined by multiplying profit per unit by
quantity sold.
P=10x
Flow chart of process of Transforming
Model Input to Output
Uncontrollable Inputs
(Environmental Factors)
Controllable Inputs
(Decision Variables
Mathematical
Model
Output
(Physical Result)
Model Solution
Production
Quantity
Projected Profit
Total Hours of
Production
Feasible solution
0
0
0
Yes
1
20
10
Yes
2
30
20
Yes
3
40
30
Yes
4
60
40
yes
Report Generation
• Solution based on the quantitative analysis of
a problem.
• Helps in decision making
• Report present recommended decision
• Manager lies working on report
Quantitative methods in Practice
• Linear programming
• Integer Linear programming
• Project Scheduling(PERT/CPM)
(Program Evaluation and Review Technique,
Critical Path Method)
• Simulation
• Decision Analysis
• Forecasting
Summary
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Why we need QBA
Why Model
Types of Models
Models in Practice