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| IST3006 | Theory of Statistics | 4+0+0 | ECTS:6 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of STATISTICS and COMPUTER SCIENCES | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face | | Contact Hours | 14 weeks - 4 hours of lectures per week | | Lecturer | Prof. Dr. Zafer KÜÇÜK | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Understanding the concepts of basic statistics, interpretation and application to create the link between theory and practice |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | understand the concepts of the theory of statistics | 1,5,8,11 | 1, | | LO - 2 : | interpret the concept of statistics | 1,5,8,11 | 1, | | LO - 3 : | transfer the information they otained into practice | 1,5,8,11 | 1, | | LO - 4 : | establish statistical links between theory and application | 1,5,8,11 | 1, | | 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), LO : Learning Outcome | | |
| Sample statistics and distributions, estimation of parameters and methods, estimations and properties, hypothesis testing, Neyman-Pierson lemma, monotone likelihood ratio, likelihood ratio and same testing. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction, revising basic probability information | | | Week 2 | Revising Known distribution | | | Week 3 | The method of moment, maximum likelihood estimates | | | Week 4 | Likelihood principle, Bayes estimates | | | Week 5 | Invariance property | | | Week 6 | Least squares estimation | | | Week 7 | Revision and problem solving | | | Week 8 | Mid-term exam | | | Week 9 | Adequacy principle, exponential family | | | Week 10 | Some theorems | | | Week 11 | Some theorems | | | Week 12 | Completeness and applications | | | Week 13 | Efficiency, Cramer-rao lower limit | | | Week 14 | Wold's theorem and some examples | | | Week 15 | Rao-Cramer inequality, revision and problem solving | | | Week 16 | End-of-term exam | | | |
| 1 | Yılmaz Akdi, Matematiksel İstatistiğe Giriş, Bıçaklar Kitapevi, 2005. | | | |
| 1 | Casella, G. Ve R.L. Berger, Statistical Inference, Wadsworth&Brooks, 1990. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 12/04/2019 | 1,5 | 50 | | End-of-term exam | 16 | 31/05/2019 | 1,5 | 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 | 4 | 14 | 56 | | Sınıf dışı çalışma | 3 | 14 | 42 | | Laboratuar çalışması | 0 | 0 | 0 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 0 | 1 | 0 | | Uygulama | 0 | 0 | 0 | | Klinik Uygulama | 0 | 0 | 0 | | Ödev | 6 | 2 | 12 | | Proje | 0 | 0 | 0 | | Kısa sınav | 0 | 0 | 0 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 0 | 1 | 0 | | Diğer 1 | 0 | 0 | 0 | | Diğer 2 | 0 | 0 | 0 | | Total work load | | | 135 |
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