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| ISTL5033 | Analysis of Directional Data | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of STATISTICS and COMPUTER SCIENCES | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Orhan KESEMEN | | Co-Lecturer | Deparment Faculty Member | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this lecture is to give a comprehensive, systematic treatment of the theory and methodology of directional statistics, to teach that graphical representation and distributions of directional data, to illustrate fields of application of directional data by using real-life examples. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | Teach graphical representation of directional data | 1,2,4,9 | 1,3, | | PO - 2 : | Learn descriptive statistics of directional data | 1,2,4,9 | 1,3, | | PO - 3 : | Teach directional distributions | 1,2,4,9 | 1,3, | | PO - 4 : | Learn statistical analysis of directional data | 1,2,4,9 | 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 | | |
| Directional data and fields of application, graphical representation of directional data, descriptive statistics of directional data, directional distributions,fundamental theorems and distribution theory of directional data. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction of the directional data | | | Week 2 | Introduction of the directional data | | | Week 3 | Fields of application | | | Week 4 | Graphical representation of ungrouped directional data | | | Week 5 | Graphical representation of grouped directional data | | | Week 6 | Descriptive statistics of directional data(measures of location) | | | Week 7 | Descriptive statistics of directional data(measures of concentration &dispersion) | | | Week 8 | Directional distributions | | | Week 9 | Mid term Exam | | | Week 10 | Directional distributions | | | Week 11 | Fundamental theorems of directional data | | | Week 12 | Fundamental theorems of directional data | | | Week 13 | Distribution theory of directional data | | | Week 14 | Statistical analysis of directional data | | | Week 15 | Statistical analysis of directional data | | | Week 16 | Final Exam | | | |
| 1 | Mardia, K. V. and Jupp, P. E. (2000). Directional Statistics. John Wiley & Sons, Chichester | | | |
| 1 | Fisher, N. I. (1993). Statistical Analysis of Circular Data. Cambridge University Press, Cambridge. | | | 2 | Pewsey, A., Neuhauser, M. ¨ and Ruxton, G. D. (2013). Circular statistics in R. Oxford University Press. | | | 3 | Watson, G. S. (1983). Statistics on Spheres. John Wiley and Sons, New York. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 1 | 30 | | Homework/Assignment/Term-paper | 14 | | 4 | 20 | | End-of-term exam | 16 | | 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 | 3 | 5 | 15 | | Arasınav için hazırlık | 3 | 8 | 24 | | Arasınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 3 | 6 | 18 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 101 |
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