|
|
| ITEO5025 | Applied Economics - I | 3+0+0 | ECTS:7.5 | | Year / Semester | Fall Semester | | Level of Course | Second Cycle | | Status | Elective | | Department | DEPARTMENT of ECONOMICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Doç. Dr. Osman Murat TELATAR | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | the aim of this course is to establish economic models and to perform econometric analysis |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | learn what econometric analysis methods are | 1,3 | 1, | | PO - 2 : | learn how econometric modeling is done. | 2,3 | 1, | | PO - 3 : | learn the estimation of economic models with econometric analysis methods | 5,7 | 1, | | PO - 4 : | learn how to analyze economic events with econometric analysis methods | 1,7 | 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), PO : Learning Outcome | | |
| descriptive statistics, simple linear regression model, least squares method, multiple linear regression model, multicolinearity, autocorrelation, heteroscedasticity |
| |
| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | fundamentals of some software packages (EViews, SPSS, Microfit) | | | Week 2 | descriptive statistics | | | Week 3 | simple linear regression model | | | Week 4 | least squares method | | | Week 5 | properties of least squares estimators | | | Week 6 | interval estimation and hypothesis testing | | | Week 7 | multiple regression model | | | Week 8 | statistical properties of estimators and interval estimation in multiple regression | | | Week 9 | Mid-term exam | | | Week 10 | model evaluation criteria in multiple regression
| | | Week 11 | multicolinearity | | | Week 12 | eliminating of multicolinearity
| | | Week 13 | autocorrelation | | | Week 14 | eliminating of autocorrelation | | | Week 15 | heteroscedasticity, eliminating of heteroscedasticity | | | Week 16 | end of term exam | | | |
| 1 | Yamak, R. ve Köseoğlu, M. 2015; Uygulamalı İstatistik ve Ekonometri, Aksakal Yayınları, Trabzon. | | | 2 | Sevüktekin, M. 2013; Ekonometriye Giriş Teori ve Uygulamalar, 1. Baskı, DORA Yayınevi, Bursa. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | /11/2021 | 2 | 30 | | In-term studies (second mid-term exam) | 13 | /12/2021 | 1 | 20 | | End-of-term exam | 16 | /01/2022 | 2 | 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 | 6 | 14 | 84 | | Arasınav için hazırlık | 6 | 4 | 24 | | Arasınav | 2 | 1 | 2 | | Kısa sınav | 1 | 1 | 1 | | Dönem sonu sınavı için hazırlık | 11 | 6 | 66 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 1 | 4 | 4 | | Total work load | | | 225 |
|