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 Coordinator
Course Lecturer(s)	Specialist Bora Güngören
Course Assistants
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; Upon the completion of this course, the student will be able to: 1.Define the advance econometric techniques, 2.Equilibrium solution by using the advance mathematical techniques. By using this solutions constructing econometric models. 3.analyze and critically evaluate from oral written, and visual materials.
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
#	Program Qualifications / Competencies	1	2	3	4	5
1	Having the conceptual and applied knowledge about the basic functions of the business and gaining the ability to use the knowledge
2	To be able to diagnose the problems related to the field of business, to use scientific approaches effectively in the solution of problems and decision-making processes.
3	To be able to reveal and analyze the environmental, social, global effects and legal consequences of the applications related to the basic functions of the business.
4	To be able to analyze information and reports that concern businesses at the national, regional and global level, to set strategic goals according to the results obtained
5	Gain the ability to use, report and interpret Business Information Systems and sub-modules required by business management
6	Planning necessary activities such as starting a new business with innovative and creative thinking and taking risks for the sustainability of the business, finding resources, making market analysis, preparing a business plan, and using the learned information in this direction.
7	Being aware of the fact that the research and learning process continues throughout life, to be able to follow the scientific and technological developments related to the business, to support oneself and the organization in innovation and continuous development.
8	To have the necessary leadership and managerial skills to achieve business objectives effectively and efficiently.
9	To be able to conduct scientific research in the field of business and report the results of the research to be used in managerial decision-making processes.
10	To be able to transfer information about the field of business using effective verbal, written and visual communication methods in the language of learning and professional English
11	To be aware of professional ethics, environmental awareness, sustainability, social responsibility, cultural, social and universal values
12	Working effectively with different disciplines or multicultural teams, taking responsibility, making risk analysis, adapting to change, critical thinking and using initiative in problem solving
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