Faculty Of Economıc, Admınıstratıve And Socıal Scıences
Busıness Admınıstratıon ( Englısh )
Course Information
NUMERICAL METHODS | |||||
---|---|---|---|---|---|
Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
Hour / Week | |||||
MAN306 | Spring | 3 | 0 | 3 | 5 |
Prerequisites and co-requisites | None |
---|---|
Language of instruction | English |
Type | Required |
Level of Course | Bachelor's |
Lecturer | Assist.Prof.Dr. Ayhan DEMİRCİ |
Mode of Delivery | Face to Face |
Suggested Subject | None |
Professional practise ( internship ) | None |
Objectives of the Course | To provide an introduction to some concepts of probability theory and statistics, and also decision theory and multi criteria decision making with applications of enterprises problems. |
Contents of the Course | Permutations, Combinatins, Probability, Discrete and Continuous random variables with their probability distributions and expectations, Samping distributions. |
Learning Outcomes of Course
# | Learning Outcomes |
---|---|
1 | will be able to define knowledge about sets. |
2 | will be able to define knowledge about probability theory. |
3 | will be able to apply probability distributions. |
4 | will be able to define decision theory and utility. |
5 | will be able to define linear programming models. |
6 | will be able to define data envelopment analysis. |
7 | will be able to define analytical hierarchic prosess. |
8 | will be able to define basics of project management. |
Course Syllabus
# | Subjects | Teaching Methods and Technics |
---|---|---|
1 | Sets and Probability Theory | Lecturing, Discussion |
2 | Sets and Probability Theory | Lecturing, Discussion |
3 | Probability Theory - Binomial Probability Distribution | Lecturing, Problem Solving |
4 | Probability Theory - Poisson Probability Distribution | Lecturing, Problem Solving |
5 | Probability Theory - Hypergeometric Probability Distribution | Lecturing, Problem Solving |
6 | Probability Theory - Geometric Probability Distribution | Lecturing, Problem Solving |
7 | Probability Theory - Normal Distribution | Lecturing, Problem Solving |
8 | Mid-Term Exam. | Written exam |
9 | Decision Theory and Utilty | Lecturing, Problem Solving |
10 | Linear Programing | Lecturing, Problem Solving |
11 | Linear Programing | Lecturing, Problem Solving |
12 | Data Envelopment Analysis | Lecturing, Problem Solving |
13 | Analytical Hierarchy Prosess | Lecturing, Problem Solving |
14 | Project Management | Lecturing, Problem Solving |
15 | General Evaluation | Lecturing, Problem Solving |
16 | Final Exam | Written exam |
Course Syllabus
# | Material / Resources | Information About Resources | Reference / Recommended Resources |
---|---|---|---|
1 | Basic Statistics for Business and Economics | Earl K.Bowen Martin K.Starr | Reference Textbook |
2 | Introduction to Statistics | David R.Anderson Dennis J. Sweeney | Suggested Textbook |
3 | Elementary Statistics | Allan G.Bluman | Suggested Textbook |
Method of Assessment
# | Weight | Work Type | Work Title |
---|---|---|---|
1 | 40% | Mid-Term Exam | Mid-Term Exam |
2 | 60% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
# | Learning Outcomes | Program Outcomes | Method of Assessment |
---|---|---|---|
1 | will be able to define knowledge about sets. | 3͵4͵7 | 1͵2 |
2 | will be able to define knowledge about probability theory. | 3͵4͵7 | 1͵2 |
3 | will be able to apply probability distributions. | 3͵4͵7 | 1͵2 |
4 | will be able to define decision theory and utility. | 3͵4͵7 | 1͵2 |
5 | will be able to define linear programming models. | 3͵4͵7 | 1͵2 |
6 | will be able to define data envelopment analysis. | 3͵4͵7 | 1͵2 |
7 | will be able to define analytical hierarchic prosess. | 3͵4͵7 | 1͵2 |
8 | will be able to define basics of project management. | 3͵4͵7 | 1͵2 |
Work Load Details
# | Type of Work | Quantity | Time (Hour) | Work Load |
---|---|---|---|---|
1 | Course Duration | 14 | 3 | 42 |
2 | Course Duration Except Class (Preliminary Study, Enhancement) | 14 | 3 | 42 |
3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
5 | Document/Information Listing | 0 | 0 | 0 |
6 | Workshop | 0 | 0 | 0 |
7 | Preparation for Midterm Exam | 1 | 16 | 16 |
8 | Midterm Exam | 1 | 2 | 2 |
9 | Quiz | 0 | 0 | 0 |
10 | Homework | 2 | 9 | 18 |
11 | Midterm Project | 0 | 0 | 0 |
12 | Midterm Exercise | 0 | 0 | 0 |
13 | Final Project | 0 | 0 | 0 |
14 | Final Exercise | 0 | 0 | 0 |
15 | Preparation for Final Exam | 1 | 27 | 27 |
16 | Final Exam | 1 | 3 | 3 |
150 |