| INDUSTRIAL ENGINEERING (ENGLISH, THESIS) | |||||
| Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| INE6103 | Multivariate Data Analysis | Spring | 3 | 0 | 3 | 9 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | English |
| Type of course: | Departmental Elective |
| Course Level: | |
| Mode of Delivery: | Face to face |
| Course Coordinator : | |
| Course Lecturer(s): |
Prof. Dr. SELİM ZAİM Assoc. Prof. YÜCEL BATU SALMAN |
| Recommended Optional Program Components: | None |
| Course Objectives: | The purpose of this doctorate course is to broaden and enrich the student's knowledge and understanding of various topics in multivariate analysis and to provide some practical experience in their applications and interpretation. The focus will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. |
|
The students who have succeeded in this course; 1. Develop skills with a range of procedures and programs for multivariate data analysis. 2. Determine which multivariate technique is appropriate for a specific research problem. |
| This course covers linear regression models, multiple regression models, dummy variable regression models, multicollinearity and its remedial measures, and multivariate statistical techniques such as; structural equation modelling, factor analysis, analysis of covariance and discriminant analysis. |
| Week | Subject | Related Preparation |
| 1) | Introduction to course | |
| 2) | Data examination and fundamentals of data manipulation | |
| 3) | Multiple Regression analysis | |
| 4) | Exploratory factor analysis | |
| 5) | Covariance based structural equation modeling technique | |
| 6) | Confirmatory factor analysis | |
| 7) | Review, Midterm Exam | |
| 8) | Path analysis using covariance based structural equation modeling technique | |
| 9) | Variance based structural equation modeling technique | |
| 10) | Path analysis using variance based structural equation modeling technique | |
| 11) | Neural network analysis | |
| 12) | Discriminant analysis | |
| 13) | Cluster analysis | |
| 14) | Review, Problem Session |
| Course Notes / Textbooks: | • Multivariate Data Analysis by Joseph F. Hair, Jr,, William C. Black, Barry J. Babin, Rolph E. Anderson, 7/E, Pearson, 2010. • Applied Multivariate Techniques by Subhash Sharma. John Wiley & Sons, Inc. 1996. • Regression Analysis by Example by Samprit Chatterjee and Ali S. Hadi. John Wiley & Sons, Inc. 2006. |
| References: | Various |
| 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 | Duration (Hours) | Workload |
| Course Hours | 13 | 3 | 39 |
| Study Hours Out of Class | 14 | 6 | 84 |
| Homework Assignments | 5 | 5 | 25 |
| Midterms | 1 | 15 | 15 |
| Final | 1 | 25 | 25 |
| Total Workload | 188 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Follows the scientific literature, analyzes it critically, and uses it effectively in solving engineering problems. | |
| 2) | Designs, plans, implements, and manages original projects related to the program field. | |
| 3) | Independently conducts studies related to the program field, assumes scientific responsibility, and evaluates the results with a critical perspective. | |
| 4) | Presents the results of their research and projects effectively in written, oral, and visual formats in accordance with academic standards. | |
| 5) | Conducts independent research on subjects requiring expertise in their field, develops original ideas, and transfers this knowledge into practice. | |
| 6) | Effectively uses advanced theoretical and practical knowledge specific to the program field. | |
| 7) | Acts in accordance with professional, scientific, and ethical values; takes responsibility by considering the social, environmental, and ethical impacts of engineering practices. |