| Management Information Systems | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code: | YBS310 | ||||
| Course Name: | Numerical Decision Making Methods | ||||
| Semester: | Spring | ||||
| Course Credits: |
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| Language of instruction: | Turkish | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Compulsory Courses | ||||
| Course Level: |
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| Mode of Delivery: | Face to face | ||||
| Course Coordinator: | Doç. Dr. ŞEBNEM ÖZDEMİR | ||||
| Course Lecturer(s): | Doç. Dr. Okan Yaşar | ||||
| Course Assistants: |
| Course Objectives: | Quantitative methods and spreadsheet skills to support management practice and decision making. Topics include statistical hypothesis testing, confidence intervals, regression analysis, optimization modeling, decision analysis and risk analysis. Therefore, this course develops quantitative methods and spreadsheet skills to support management practice and decision making including: hypothesis testing, confidence intervals, regression analysis, decision analysis, optimization and risk analysis. The course goals are: 1) Demonstrate the wide range of situations in which quantitative analysis improves decision making and creates competitive advantages; 2) Develop students’ analytical thinking skills. 3) Develop mastery of analysis using spreadsheet models, and effective communication of results. |
| Course Content: | Upon completing the course, the student should be able to: 1. Describe a set of data using histograms, scatter diagrams and summary statistics. 2. Compute statistics from sample data to support confidence interval estimation, hypothesis testing and regression analysis. 3. Infer the statistical precision of insights derived from confidence interval estimation, hypothesis testing and regression analysis. 4. Construct effective models of decision making situations using principles of professional spreadsheet design. 5. Compute optimal solutions to decision making models for the management of a wide range of situations in which quantitative analysis improves decision making. 6. Analyze spreadsheet simulation models and decisions with uncertain outcomes by using multiple criteria for optimality and risk. |
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The students who have succeeded in this course;
1) 1. Describe a set of data using histograms, scatter diagrams and summary statistics. 2. Compute statistics from sample data to support confidence interval estimation, hypothesis testing and regression analysis. 3. Infer the statistical precision of insights derived from confidence interval estimation, hypothesis testing and regression analysis. 4. Construct effective models of decision making situations using principles of professional spreadsheet design. 5. Compute optimal solutions to decision making models for the management of a wide range of situations in which quantitative analysis improves decision making. 6. Analyze spreadsheet simulation models and decisions with uncertain outcomes by using multiple criteria for optimality and risk. 2) 2. Compute statistics from sample data to support confidence interval estimation, hypothesis testing and regression analysis. 3) 3. Infer the statistical precision of insights derived from confidence interval estimation, hypothesis testing and regression analysis. 4) 4. Constructing effective models of decision making situations using principles of professional spreadsheet design. |
| Week | Subject | Related Preparation |
| 1) | Chapter 1 (Introduction to Quantitative Analysis) | |
| 2) | Chapter 2 (Probability Concepts and Applications) | |
| 3) | Chapter 2 (Probability Concepts and Applications) | |
| 4) | Estimation & Confidence Intervals | |
| 5) | Estimation & Confidence Intervals | |
| 6) | Chapter (Regression Models) | |
| 7) | Chapter (Regression Models) | |
| 8) | Chapter (Decision Analysis) | |
| 9) | Linear Programming Models: Graphical & Computer Methods | |
| 10) | Linear Programming Applications | |
| 11) | Simulation Modeling | |
| 11) | Simulation Modeling | |
| 12) | Introduction to probability, Bayes’ Theorem | |
| 13) | Introduction to probability, Bayes’ Theorem | |
| 14) | Game theory |
| Course Notes / Textbooks: | 1. Anderson, D., Sweeney, D., & Williams, T. (2019). Modern İşletmecilik İçin İstatistiksel Teknikler. 2. Triantaphyllou, E. (2000). Çok Kriterli Karar Yapma Yöntemleri: Bir Genel Bakış ve Karşılaştırmalı Analiz. |
| References: | 1. Bazerman, M., & Moore, D. A. (2012). Karar Verme Yönetimi. 2. Saaty, T. L. (2008). Karar Verme İçin Analitik Hiyerarşi Süreci. |
| Course Learning Outcomes | 1 |
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3 |
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| Program Outcomes | |||||||||||||
| 1) It has a wide range of interdisciplinary approaches to management information systems, primarily business and computer engineering. | 3 | 2 | 3 | 2 | |||||||||
| 2) Comprehends the management information systems in terms of technical, organizational and managerial aspects and uses the current programming language by knowing the logic of programming. | 1 | 1 | 2 | 3 | |||||||||
| 3) Uses different information technologies and systems for understanding and solving various business problems. | 2 | 3 | 2 | 3 | |||||||||
| 4) Interpret the data, concepts and ideas in the field of management information systems with scientific and technological methods. | 3 | 3 | 2 | 2 | |||||||||
| 5) Analyze the needs for an information system and analyze the processes of analysis, design and implementation of the database. | 1 | 3 | 2 | 2 | |||||||||
| 6) Gains technical and managerial contributions to IT projects and takes responsibility. | 2 | 3 | 2 | 3 | |||||||||
| 7) Solve complex business and informatics problems by using various statistical techniques and numerical methods and make analyzes using statistical programs effectively. | 3 | 2 | 2 | 3 | |||||||||
| 8) Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | 2 | 2 | 1 | 3 | |||||||||
| 9) Develops teamwork, negotiation, leadership and entrepreneurship skills. | 2 | 2 | 2 | 3 | |||||||||
| 10) Has universal ethical values, social responsibility awareness and sufficient legal knowledge. | 3 | 2 | 2 | 2 | |||||||||
| 11) Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | 3 | 3 | 3 | 1 | |||||||||
| 12) Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms. | 3 | 2 | 3 | 2 | |||||||||
| 13) It uses information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field. | 2 | 1 | 2 | 3 | |||||||||
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | It has a wide range of interdisciplinary approaches to management information systems, primarily business and computer engineering. | 3 |
| 2) | Comprehends the management information systems in terms of technical, organizational and managerial aspects and uses the current programming language by knowing the logic of programming. | 2 |
| 3) | Uses different information technologies and systems for understanding and solving various business problems. | 3 |
| 4) | Interpret the data, concepts and ideas in the field of management information systems with scientific and technological methods. | 2 |
| 5) | Analyze the needs for an information system and analyze the processes of analysis, design and implementation of the database. | 2 |
| 6) | Gains technical and managerial contributions to IT projects and takes responsibility. | 2 |
| 7) | Solve complex business and informatics problems by using various statistical techniques and numerical methods and make analyzes using statistical programs effectively. | 3 |
| 8) | Uses a foreign language at the B1 General Level in terms of European Language Portfolio criteria according to the level of education. | 2 |
| 9) | Develops teamwork, negotiation, leadership and entrepreneurship skills. | 3 |
| 10) | Has universal ethical values, social responsibility awareness and sufficient legal knowledge. | 3 |
| 11) | Develops positive attitudes related to lifelong learning and identifies individual learning needs and carries out studies to correct them. | 2 |
| 12) | Students will be able to communicate their ideas and solutions both written and orally, and present and publish them on both national and international platforms. | 2 |
| 13) | It uses information and communication technologies together with computer software at the advanced level of European Computer Driving License required by the field. | 3 |
| Semester Requirements | Number of Activities | Level of Contribution |
| Midterms | 1 | % 40 |
| Final | 1 | % 60 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 40 | |
| PERCENTAGE OF FINAL WORK | % 60 | |
| total | % 100 | |
| Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
| Course Hours | 14 | 2 | 3 | 70 | |||
| Midterms | 1 | 20 | 2 | 22 | |||
| Final | 1 | 30 | 3 | 33 | |||
| Total Workload | 125 | ||||||