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| EKO5660 | Mathematical Statistics - II | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Mustafa KÖSEOĞLU | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The objective of the course is to acquaint beginning graduate students in econometrics and other disciplines with the concepts of probability and mathematical development of statistics. To provide a foundation for further study in probability theory and statistical theory at both masters and doctoral levels. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | know the fundamental principles of statistics and probability which underlie all statistical research and application | 5,8 | 1,3, | | PO - 2 : | carry out elementary data analyses | 5,8 | 1,3 | | PO - 3 : | use statistical package | 5,8 | 1,3 | | PO - 4 : | criticize the use of statistical methods in research papers in own area | 5,8 | 1,3 | | PO - 5 : | understand and implement basics ideas of study design | 5,8 | 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 | | |
| Basic elements of statistical analysis; statistical inference including estimation and tests of hypotheses; regression, correlation and analysis of variance; central limit theorem and laws of large numbers |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Random variables functions | | | Week 2 | Sampling distributions | | | Week 3 | Sampling distributions | | | Week 4 | Game theory | | | Week 5 | Game theory | | | Week 6 | Estimation theory | | | Week 7 | Estimation theory | | | Week 8 | Hypothesis testing | | | Week 9 | Mid-term exam | | | Week 10 | Hypothesis testing | | | Week 11 | Analysis of variance | | | Week 12 | Quiz | | | Week 13 | Chi-square test | | | Week 14 | Chi-square test | | | Week 15 | Analysis of regression and correlation | | | Week 16 | End-of-term exam | | | |
| 1 | Irvin, M. and Marylees, M., (Çev. Ümit Şenesen) 2002; Matematiksel istatistik, İstanbul | | | 2 | Hogg, R. V., and Craig, A. T., 1978; Introduction to Mathematical statistics, Macmillian Publishing Co., Inc., New York. | | | |
| 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 | 1,25 | 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 | 10 | 14 | 140 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 1 | 1 | 1 | | Ödev | 4 | 1 | 4 | | Kısa sınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 26 | 1 | 26 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 225 |
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