Course Detail
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
QUANTITATIVE METHODS for BUSINESS DECISION MAKING | - | Fall Semester | 3+0 | 3 | 5 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Required |
Course Coordinator | Assist.Prof. Esra BAYTÖREN |
Name of Lecturer(s) | Assist.Prof. Esra BAYTÖREN |
Assistant(s) | |
Aim | The aim of this course is to ensure that students have the necessary qualifications and infrastructure to formulate and solve business decision problems using quantitative techniques such as single and multi-criteria decision analysis, Markov analysis, and simulation modeling. |
Course Content | This course contains; Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty),Utility Theory, Rationality and Decision Making,Decision Making Under Ignorance (Uncertainty),Decision Making Under Risk,Multi-Stage Decisions and Decision Trees,Bayesian Decision Analysis,Game Theory,Markov Analysis,Group Decisions and Social Choice,Multi-Criteria Decision Making - Basic Concepts,Multi-Criteria Decision Making - Analytic Hierarchy Process,Multi-Criteria Decision Making - Analytic Network Process,Data Envelopment Analysis,Simulation - Basic Concepts and Applications. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
1. Will be able to describe the elements of decision theory and the distinction between individual and group decisions. | 10, 12, 16, 9 | A, E |
1.1 Explains what should be taken into consideration when determining the objective, alternatives and states of the nature for a decision process | ||
1.2 Describes the characteristics of both individual and group decisions | ||
2. Will be able to realize the solutions of decision making under uncertainty and risk. | 10, 12, 16, 9 | A, E |
2.1 Uses such basic strategies as maximin, maximax, and regret criteria for decision problems under uncertainty | ||
2.2 Uses such basic strategies as expected value, maximum likelihood, and expected value of perfect information for decision problems under risk | ||
3. Will be able to express the value of experimentation in decision process. | 10, 12, 16, 9 | A, E |
3.1 Constructs probability tree diagrams | ||
3.2 Estimates revise probability using Bayesian analysis | ||
4. Will be able to determine future states or conditions by using Markov analysis. | 10, 12, 16, 9 | A, E |
4.1 Explains the place of Markov process models in decision processes | ||
4.2 Computes long-term ( steady-state) conditions by using the transition matrix probabilities | ||
5. Will be able to design multi-criteria decision problems. | 10, 12, 16, 9 | A, E |
5.1 Explains the importance of building decision frame for a multicriteria decision making problem | ||
5.2 Uses such techniques as AHP, ANP, Topsis, and Vitor for multicriteria decision making process | ||
6. Will be able to explain the advantages and disadvantages of simulation. | 10, 12, 16, 9 | A, E |
6.1 Identifies the necessity of simulation technique in a decision process | ||
6.2 Constructs simple simulation models using Excel |
Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 16: Question - Answer Technique, 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, E: Homework |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty) | |
2 | Utility Theory, Rationality and Decision Making | |
3 | Decision Making Under Ignorance (Uncertainty) | |
4 | Decision Making Under Risk | |
5 | Multi-Stage Decisions and Decision Trees | |
6 | Bayesian Decision Analysis | |
7 | Game Theory | |
8 | Markov Analysis | |
9 | Group Decisions and Social Choice | |
10 | Multi-Criteria Decision Making - Basic Concepts | |
11 | Multi-Criteria Decision Making - Analytic Hierarchy Process | |
12 | Multi-Criteria Decision Making - Analytic Network Process | |
13 | Data Envelopment Analysis | |
14 | Simulation - Basic Concepts and Applications |
Resources |
[1] Quantitative Analysis for Management, B.Render & R.M.Stair & M.E.Hanna, 11th Edition, Pearson, 2012 [2] An Introduction to Decision Theory, Martin Peterson, Cambridge University Press, 2009 [3] Multi-Criteria Decision Making Methods: A Comparative Study, Panos M. Pardalos ve Donald Hearn (Editors), Springer Science+Business Media Dordrecht, 2000 |
[4] Lecture Notes [5] Çok Kriterli Karar Verme Yöntemleri, B.Fatih Yıldırım ve Emrah Önder (Editörler), 2.Baskı, Dora Yayınları, 2015 [6] Karar Teorisi, Zerrin Aladağ, 2. Baskı, Umuttepe Yayınlar, 2014 [7] Karar Verme, Mustafa Aytaç ve Necmi Gürsakal (Editörler), Dora Yayınları, 2015 |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | Defines the theoretical issues in the field of information and management. | ||||||
2 | Describes the necessary mathematical and statistical methods in the field of information and management. | X | |||||
3 | Uses at least one computer program in the field of information and management. | X | |||||
4 | Sustains proficiency in a foreign language requiredor information and management studies. | X | |||||
5 | Prepares informatics/software projects and work in a team. | ||||||
6 | Constantly updates himself / herself by following developments in science and technology with an understanding of the importance of lifelong learning through critically evaluating the knowledge and skills that s/he has got.7. Uses theoretical and practical expertise in the field of information and management | ||||||
7 | Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication skills. | X | |||||
8 | Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication. | X | |||||
9 | Adopts organizational / institutional and social ethical values. | ||||||
10 | Within the framework of community involvement adopts social responsibility principles and takes initiative when necessary. | ||||||
11 | Uses and analyses basic facts and data in various disciplines (economics, finance, sociology, law, business) in order to conduct interdisciplinary studies. | X | |||||
12 | Writes software in different platforms such as desktop, mobile, web on its own and / or in a team. |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 40 | |
Rate of Final Exam to Success | 60 | |
Total | 100 |
ECTS / Workload Table | ||||||
Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
Course Hours | 14 | 3 | 42 | |||
Guided Problem Solving | 0 | 0 | 0 | |||
Resolution of Homework Problems and Submission as a Report | 2 | 25 | 50 | |||
Term Project | 0 | 0 | 0 | |||
Presentation of Project / Seminar | 0 | 0 | 0 | |||
Quiz | 0 | 0 | 0 | |||
Midterm Exam | 0 | 0 | 0 | |||
General Exam | 1 | 58 | 58 | |||
Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
Total Workload(Hour) | 150 | |||||
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(150/30) | 5 | |||||
ECTS of the course: 30 hours of work is counted as 1 ECTS credit. |
Detail Informations of the Course
Course Description
Course | Code | Semester | T+P (Hour) | Credit | ECTS |
---|---|---|---|---|---|
QUANTITATIVE METHODS for BUSINESS DECISION MAKING | - | Fall Semester | 3+0 | 3 | 5 |
Course Program |
Prerequisites Courses | |
Recommended Elective Courses |
Language of Course | English |
Course Level | First Cycle (Bachelor's Degree) |
Course Type | Required |
Course Coordinator | Assist.Prof. Esra BAYTÖREN |
Name of Lecturer(s) | Assist.Prof. Esra BAYTÖREN |
Assistant(s) | |
Aim | The aim of this course is to ensure that students have the necessary qualifications and infrastructure to formulate and solve business decision problems using quantitative techniques such as single and multi-criteria decision analysis, Markov analysis, and simulation modeling. |
Course Content | This course contains; Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty),Utility Theory, Rationality and Decision Making,Decision Making Under Ignorance (Uncertainty),Decision Making Under Risk,Multi-Stage Decisions and Decision Trees,Bayesian Decision Analysis,Game Theory,Markov Analysis,Group Decisions and Social Choice,Multi-Criteria Decision Making - Basic Concepts,Multi-Criteria Decision Making - Analytic Hierarchy Process,Multi-Criteria Decision Making - Analytic Network Process,Data Envelopment Analysis,Simulation - Basic Concepts and Applications. |
Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
1. Will be able to describe the elements of decision theory and the distinction between individual and group decisions. | 10, 12, 16, 9 | A, E |
1.1 Explains what should be taken into consideration when determining the objective, alternatives and states of the nature for a decision process | ||
1.2 Describes the characteristics of both individual and group decisions | ||
2. Will be able to realize the solutions of decision making under uncertainty and risk. | 10, 12, 16, 9 | A, E |
2.1 Uses such basic strategies as maximin, maximax, and regret criteria for decision problems under uncertainty | ||
2.2 Uses such basic strategies as expected value, maximum likelihood, and expected value of perfect information for decision problems under risk | ||
3. Will be able to express the value of experimentation in decision process. | 10, 12, 16, 9 | A, E |
3.1 Constructs probability tree diagrams | ||
3.2 Estimates revise probability using Bayesian analysis | ||
4. Will be able to determine future states or conditions by using Markov analysis. | 10, 12, 16, 9 | A, E |
4.1 Explains the place of Markov process models in decision processes | ||
4.2 Computes long-term ( steady-state) conditions by using the transition matrix probabilities | ||
5. Will be able to design multi-criteria decision problems. | 10, 12, 16, 9 | A, E |
5.1 Explains the importance of building decision frame for a multicriteria decision making problem | ||
5.2 Uses such techniques as AHP, ANP, Topsis, and Vitor for multicriteria decision making process | ||
6. Will be able to explain the advantages and disadvantages of simulation. | 10, 12, 16, 9 | A, E |
6.1 Identifies the necessity of simulation technique in a decision process | ||
6.2 Constructs simple simulation models using Excel |
Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 16: Question - Answer Technique, 9: Lecture Method |
Assessment Methods: | A: Traditional Written Exam, E: Homework |
Course Outline
Order | Subjects | Preliminary Work |
---|---|---|
1 | Decision Theory - Basic Concepts, Characteristics of Decision Problemlems, and Decision Environments (Risk, Ignorance, Uncertainty) | |
2 | Utility Theory, Rationality and Decision Making | |
3 | Decision Making Under Ignorance (Uncertainty) | |
4 | Decision Making Under Risk | |
5 | Multi-Stage Decisions and Decision Trees | |
6 | Bayesian Decision Analysis | |
7 | Game Theory | |
8 | Markov Analysis | |
9 | Group Decisions and Social Choice | |
10 | Multi-Criteria Decision Making - Basic Concepts | |
11 | Multi-Criteria Decision Making - Analytic Hierarchy Process | |
12 | Multi-Criteria Decision Making - Analytic Network Process | |
13 | Data Envelopment Analysis | |
14 | Simulation - Basic Concepts and Applications |
Resources |
[1] Quantitative Analysis for Management, B.Render & R.M.Stair & M.E.Hanna, 11th Edition, Pearson, 2012 [2] An Introduction to Decision Theory, Martin Peterson, Cambridge University Press, 2009 [3] Multi-Criteria Decision Making Methods: A Comparative Study, Panos M. Pardalos ve Donald Hearn (Editors), Springer Science+Business Media Dordrecht, 2000 |
[4] Lecture Notes [5] Çok Kriterli Karar Verme Yöntemleri, B.Fatih Yıldırım ve Emrah Önder (Editörler), 2.Baskı, Dora Yayınları, 2015 [6] Karar Teorisi, Zerrin Aladağ, 2. Baskı, Umuttepe Yayınlar, 2014 [7] Karar Verme, Mustafa Aytaç ve Necmi Gürsakal (Editörler), Dora Yayınları, 2015 |
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications | |||||||
No | Program Qualification | Contribution Level | |||||
1 | 2 | 3 | 4 | 5 | |||
1 | Defines the theoretical issues in the field of information and management. | ||||||
2 | Describes the necessary mathematical and statistical methods in the field of information and management. | X | |||||
3 | Uses at least one computer program in the field of information and management. | X | |||||
4 | Sustains proficiency in a foreign language requiredor information and management studies. | X | |||||
5 | Prepares informatics/software projects and work in a team. | ||||||
6 | Constantly updates himself / herself by following developments in science and technology with an understanding of the importance of lifelong learning through critically evaluating the knowledge and skills that s/he has got.7. Uses theoretical and practical expertise in the field of information and management | ||||||
7 | Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication skills. | X | |||||
8 | Follows up-to-date technology using a foreign language at least A1 level, holds verbal / written communication. | X | |||||
9 | Adopts organizational / institutional and social ethical values. | ||||||
10 | Within the framework of community involvement adopts social responsibility principles and takes initiative when necessary. | ||||||
11 | Uses and analyses basic facts and data in various disciplines (economics, finance, sociology, law, business) in order to conduct interdisciplinary studies. | X | |||||
12 | Writes software in different platforms such as desktop, mobile, web on its own and / or in a team. |
Assessment Methods
Contribution Level | Absolute Evaluation | |
Rate of Midterm Exam to Success | 40 | |
Rate of Final Exam to Success | 60 | |
Total | 100 |