COURSE UNIT TITLE

: QUANTATIVE BUSINESS ANALYSIS I

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ENM 5013 QUANTATIVE BUSINESS ANALYSIS I ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ADIL BAYKASOĞLU

Offered to

ENGINEERING MANAGEMENT- NON THESIS (EVENING PROGRAM)

Course Objective

This course provides students with the analytical tools necessary to make better management decisions. In order to appraise and evaluate quantitative information, several mathematical techniques are introduced that can be applied to business situations. Since spreadsheets are the dominant tool in business and they are flexible and powerful platform for analyzing data and modeling business processes and decisions, spreadsheets will be used primarily. The focus of this course is on exploiting the power of quantitative models and optimizations systems in problem solving.

Learning Outcomes of the Course Unit

1   This course is expected to help the student to learn basic principles of quantitative models and optimization techniques in management decisions.
2   To enable students to model real life business problems via linear and integer programming.
3   To enable students to solve these models through optimization softwares such as LINGO, OPL Studio etc.
4   To enable students to analyze and interpret the solutions of these models by using sensitivity analysis

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Modeling and Management Science
2 Model building in Management Science
3 Introduction to Linear Programming (LP)
4 Modeling and Solving LP problems with Computer Applications
5 Modeling and Solving LP problems with Computer Applications
6 Modeling and Solving LP problems with Computer Applications
7 Sensitivity Analysis
8 Game Theory
9 Midterm
10 Integer Linear Programming
11 Integer Linear Programming
12 Applications of LP (DEA, C/B analyses etc.)
13 Case discussions & Project Presentations
14 Case discussions & Project Presentations

Recomended or Required Reading

C. T., Ragsdale, Spreadsheet Modeling and Decision Analysis, 4e, South-Western College Publishing, 2004

Planned Learning Activities and Teaching Methods

Class presentations, case studies and practical applications.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.25 + ASG *0.25 +FIN *0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG *0.25 +RST *0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm : 25%
Final Term: 50%
Homework: 25%

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Prof.Dr.Adil Baykasoğlu
+90 232 301 76 00

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 7 91
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparing presentations 1 30 30
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 206

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.12144
LO.25453
LO.3333
LO.44122

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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