ECTS - Advance Data Modeling
Advance Data Modeling (ECON552) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advance Data Modeling | ECON552 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Ph.D. |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| Course Objectives | This course provides an understanding of the application of software technologies that enables users to make better and faster decisions based on various data. This course covers the statistical tools needed to understand empirical research and to plan and execute independent research projects. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of policies and programs. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Single-Equation Regression Models Two-Variable Regression Model: The Problem of Estimation | DG and DCP Chp 1. |
| 2 | Classical Normal Linear Regression Model (CNLRM) | DG and DCP Chp 2-3. |
| 3 | Multiple Regression Analysis: The Problem of Inference | DG and DCP Chp 3-8. |
| 4 | The Matrix Approach to Linear Regression Model | JJ and JD Chp 3. |
| 5 | Relaxing the Assumptions of the Classical Model MIDTERM EXAM I | DG and DCP Chp 10-13. JJ and JD Chp 6. |
| 6 | Nonlinear Regression Models | DG and DCP Chp 14. |
| 7 | Qualitative Response Regression Models | DG and DCP Chp 15. JJ and JD Chp 13. |
| 8 | Panel Data Regression Models | DG and DCP Chp 16. JJ and JD Chp 12. |
| 9 | Dynamic Econometric Models: Autoregressive and Distributed-Lag Models | DG and DCP Chp 17. JJ and JD Chp 8. |
| 10 | Simultaneous-Equation Models | DG and DCP Chp 18-20. |
| 11 | Time Series Analysis | DG and DCP Chp 21-22. JJ and JD Chp 8-9. |
| 12 | Panel Time Series Models | SRP and AM |
| 13 | Nonlinear Modelling in Time and Panel data analysis | TT and GCEJ |
| 14 | FINAL EXAM |
Sources
| Course Book | 1. Domador Gujarati, Dawn C. Porter (2015) Introduction to Econometrics McGraw Hill Higher Education; 5th edition |
|---|---|
| 2. Jack Johnston and John Dinardo Econometric Methods. McGraw Hill Higher Education; 4th edition | |
| 3. Terasvirta T. and Granger C.E.J Modelling Nonlinear Economic Time Series | |
| 4. Smith R.P. and Fuertes A.M. Panel Time Series (2012) |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 14 | 10 |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | 2 | 20 |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 20 |
| Final Exam/Final Jury | 1 | 50 |
| Toplam | 18 | 100 |
| Percentage of Semester Work | |
|---|---|
| Percentage of Final Work | 100 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Is independently able to build a problem in the area of study, solve the problem by developing solution techniques and assess the solutions. | X | ||||
| 2 | Is capable of creating a groundwork in the fundamental branches of mathematics as well as in his/her research area | X | ||||
| 3 | follows the latest national and international literature in Mathematics and in his/her area of research; and uses them in his/her related studies | X | ||||
| 4 | observes and adopts the scientific ethical values in his/her professional and social life | X | ||||
| 5 | presents in Turkish and English in academic/scientific events the results of his/her research or the latest studies and findings on a special topic and participates in discussions | X | ||||
| 6 | Develops skills to work independently or as a member of a team | X | ||||
| 7 | Develops competences in the areas of creative and critical thinking, problem solving and producing original studies. Follows recent scientific studies, is capable of making an analysis, synthesis and assessment of the knowledge acquired | X | ||||
| 8 | Is open to lifelong improvement of his/her acquired knowledge, skills and competences. | X | ||||
| 9 | Is able to apply the acquired knowledge and problem-solving skills to interdisciplinary studies, proposes different solution methods to problems in terms of mathematical models and from a mathematical point of view | X | ||||
| 10 | Uses the mathematical based softwares, informatics and communication technologies for scientific purposes | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 14 | 3 | 42 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | 1 | 21 | 21 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 20 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 25 | 25 |
| Total Workload | 150 | ||