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| EKO6520 | Multivariate Statistics Methods-II | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Tuba YAKICI AYAN | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | This course aims to foster understanding of what can be learned trough correct practical application of statistical techniques to data. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | determine the appropriate multivariate analysis method to solve any problem | 3 | 4,6, | | PO - 2 : | control characteristics of data | 3 | 4,6, | | PO - 3 : | apply multivariate analysis methods to suitable data correctly | 3 | 4,6, | | PO - 4 : | interpret obtained results | 3 | 4,6, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Extreme data, outliers, Methods to fix missing data problem, Multivariate regression, Discriminant analysis, Path analysis, Logistic regression, Canonical correlation. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Extreme data and outliers. Computer analyses of sample examples. | | | Week 2 | Missing data. Computer analyses of sample examples | | | Week 3 | Computer analyses of sample examples for fixing missing data problem. | | | Week 4 | Limitations to multiple linear regression,Equations for multiple regression. Computer analyses of sample examples | | | Week 5 | Test of regression components, confidence limits, fit adequacy of model. Computer analyses of sample examples | | | Week 6 | Computer analyses of sample examples | | | Week 7 | Discriminant analysis. Computer analyses of sample examples | | | Week 8 | Computer analyses of sample examples | | | Week 9 | Mid-term exam | | | Week 10 | Path analysis. Computer analyses of sample examples | | | Week 11 | Bivariate Logistic regression. Computer analyses of sample examples | | | Week 12 | Quiz | | | Week 13 | Multiply logistic regression. Computer analyses of sample examples | | | Week 14 | Computer analyses of sample examples for multiply logistic regression | | | Week 15 | Canonical correlation analysis. Computer analyses of sample examples | | | Week 16 | End of term exam | | | |
| 1 | Tabachnick, B., G., Fidell, L. 1996; Using Multivariate Statistics, 3nd ed. , California State University, Northridge. | | | |
| 1 | Alpar, R. 2011; Çok Değişkenli İstatistiksel Yöntemler, Detay Yayıncılık, Ankara. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 04/2024 | 1 | 30 | | Homework/Assignment/Term-paper | 12 | 05/2024 | 1 | 20 | | End-of-term exam | 16 | 06/2024 | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 8 | 14 | 112 | | Arasınav için hazırlık | 12 | 2 | 24 | | Arasınav | 1 | 1 | 1 | | Ödev | 3 | 2 | 6 | | Dönem sonu sınavı için hazırlık | 13 | 3 | 39 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 225 |
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