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| ISLZ6996 | Advanced Applied Research Methods | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Compulsory | | Department | DEPARTMENT of BUSINESS ADMINISTRATION | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Hakkı YAVUZ | | Co-Lecturer | No. | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to apply apropriate advenced statistical methods used in social science. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Formulate advenced statsitical methods used in social science. | 3,8,10 | 1,3, | | PO - 2 : | Run advenced statistiacl methods in a computer by SPSS and present the outputs. | 3,8,10 | 1,3, | | PO - 3 : | Analyze model output. | 3,8,10 | 1,3, | | 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 | | |
| Multivariate statistcal assumtions and related tests, Multiple linear regression assumes and related tests, Nonlinear regression analysisi, Lojistik regression, Probit regression, Covariance analysisi, Canonik correlation ananlysisi, Principal component analysis, Multi dimensional scaling, Cluster analysisi, Discriminant anlaysisi, Comparison of dependent grups. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Assumptions and calssification of multivariate statistical methods. | | | Week 2 | Assumptions of multiple linear regression. | | | Week 3 | Tests of assumtions in Multiple linear regression. | | | Week 4 | Nonlinear regresyon. | | | Week 5 | Binary logistic regression. | | | Week 6 | Multiple logistic regression. | | | Week 7 | Cox regression. | | | Week 8 | Probit regression. | | | Week 9 | Midterm exam. | | | Week 10 | ANCOVA | | | Week 11 | Canonical orrelation. | | | Week 12 | Principal component anaylsis. | | | Week 13 | Multi dimensionnal scaling. | | | Week 14 | Cluster analysis. | | | Week 15 | Discriminant analysis. | | | Week 16 | Compairing of dependent gruops. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2 | 30 | | Homework/Assignment/Term-paper | 1314 | | 33 | 20 | | End-of-term exam | 16 | | 3 | 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 | 15 | 45 | | Sınıf dışı çalışma | 6 | 8 | 48 | | Laboratuar çalışması | 0 | 0 | 0 | | Arasınav için hazırlık | 4 | 8 | 32 | | Arasınav | 3 | 1 | 3 | | Uygulama | 0 | 0 | 0 | | Klinik Uygulama | 0 | 0 | 0 | | Ödev | 3 | 8 | 24 | | Proje | 0 | 0 | 0 | | Kısa sınav | 0 | 0 | 0 | | Dönem sonu sınavı için hazırlık | 6 | 6 | 36 | | Dönem sonu sınavı | 3 | 1 | 3 | | Diğer 1 | 5 | 5 | 25 | | Diğer 2 | 0 | 0 | 0 | | Total work load | | | 216 |
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