ECTS - Advance Data Modeling
Advance Data Modeling (ECON481) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Advance Data Modeling | ECON481 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | |
| Learning and Teaching Strategies | . |
| Course Lecturer(s) |
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| Course Objectives | The main contents are; statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of policies and programs. Students will learn the principles and best practices for how to use data in order to support fact-based decision-making. Emphasis will be given to applications in various data which has big data facilities. |
| Course Learning Outcomes |
The students who succeeded in this course;
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| 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) | JJ ve JD Bölüm 3. |
| 3 | Multiple Regression Analysis: The Problem of Inference | DG and DCP Chp 3-8. |
| 4 | The Matrix Approach to Linear Regression Model | DG and DCP Chapter 14. |
| 5 | Relaxing the Assumptions of the Classical Model | DG and DCP Chp 10-13. JJ and JD Chp 6. |
| 6 | MIDTERM EXAM I | |
| 7 | Nonlinear Regression Models | DG and DCP Chapter 16. JJ and JD Chapter 12. |
| 8 | Niteliksel Tepki Regresyon Modelleri | DG and DCP Chp. 15. JJ and JD Chp 13. |
| 9 | Panel Data Regression Models | DG and DCP Chp. 18-20. |
| 10 | Dynamic Econometric Models: Autoregressive and Distributed-Lag Models | DG and DCP Chp. 21-22. JJ and JD Chp 8-9 |
| 11 | Eşanlı Denklemler | DG and DCP Chp 18-20. |
| 12 | Time Series Analysis | DG and DCP Chp 21-22. JJ and JD Chp 8-9. |
| 13 | Panel Time Series Models | DG and DCP Chp. 3-8 |
| 14 | Nonlinear Modelling in Time and Panel data analysis | JJ and JD Chp. 3. |
| 15 | Nonlinear Modelling in Time and Panel data analysis | JJ and JD Chp. 3. |
| 16 | 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 |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | 1 | 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 | 5 | 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 | Gains the ability to use knowledge by acquiring conceptual and practical understanding of all core functions of business. | |||||
| 2 | Identifies problems related to the field of business and effectively uses scientific approaches in problem-solving and decision-making processes. | |||||
| 3 | Demonstrates and analyzes the environmental, social, global impacts and legal consequences of practices related to core business functions. | |||||
| 4 | Analyzes information and reports relevant to businesses at national, regional, and global levels, and sets strategic goals based on the results obtained. | |||||
| 5 | Gains the ability to use, report, and interpret Business Information Systems and their sub-modules required for business management. | |||||
| 6 | Plans the necessary activities such as taking risks, securing resources, conducting market analysis, and preparing business plans for starting a new venture and ensuring its sustainability with innovative and creative thinking, and applies the acquired knowledge accordingly. | |||||
| 7 | Supports oneself and the organization in terms of innovation and continuous improvement, while being aware that the process of research and learning is lifelong and following scientific and technological developments related to business. | |||||
| 8 | Acquires the necessary leadership and managerial skills to achieve business objectives effectively and efficiently. | |||||
| 9 | Conducts scientific research in the field of business and reports the research findings to be used in managerial decision-making processes. | |||||
| 10 | Uses effective verbal, written, and visual communication methods to convey information related to the field of business in the language of instruction and professional English. | |||||
| 11 | Develops awareness of professional ethics, environmental sensitivity, sustainability, social responsibility, and cultural, societal, and universal values. | |||||
| 12 | Takes initiative in working effectively with different disciplines or multicultural teams, assuming responsibility, conducting risk analysis, adapting to change, and applying critical thinking and problem-solving skills | |||||
| 13 | . | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 16 | 3 | 48 |
| Presentation/Seminar Prepration | 1 | 21 | 21 |
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 147 | ||