ECTS - Multi Dimensional Data Modeling

Multi Dimensional Data Modeling (ECON482) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Multi Dimensional Data Modeling ECON482 Area Elective 3 0 0 3 6
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
  • Specialist Bora Güngören
Course Assistants
Course Objectives The main aim of this course is to provide students with adequate knowledge in both programming in R software and theoretical multivariate statistical concepts. Hence, students will be able to use R in their multivariate statistical analysis related to their field of research.
Course Learning Outcomes The students who succeeded in this course;
  • Upon the completion of this course, the student will be able to: 1. comprehend knowledge in working with R software for multivariate statistical analysis.
  • 2. interpret the results of the research according to the multivariate statistical methods applied to data.
  • 3. utilize the R for describing and analyzing the quantitative data.
  • 4. understand and apply mathematical concepts and reasoning, analyze and interpret various types of data.
Course Content Multivariate statistics, factor analysis, principal component analysis, bootstrapping, state space analysis and Kalman Filter, Markov chain models, smooth transition, frequency domain, functional regression analysis.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Some Concepts in Multivariate statistics WWSW and KSS
2 Classification, Discrimination and Closeness WWSW and KSS
3 Factor Analysis and Principal Component Analysis WWSW and KSS
4 Bootstrapping WWSW and KSS
5 State Space Analysis and Kalman Filter WWSW, KSS and JDH
6 Midterm Exam
7 Markov Chain Models WWSW, KSS and JDH
8 Smooth Transition and Threshold Models Lecture notes available
9 Frequency Domain: Fourier Function WWSW, KSS and JDH
10 Periodgram WWSW
11 Asymptotic Concepts in N and T JDH
12 Ridge Regresyonu ve Lasso Tahmincisi Lecture notes available
13 Functional Regression Analysis Lecture notes available
14 Information Accumulated Multilayer Models (IAM) Lecture notes available
15 Information Accumulated Multilayer Models (IAM) Lecture notes available
16 Final Exam

Sources

Course Book 1. K. S. Srivastava (2002) Methods of Multivariate Statistics. Wiley Series in probability and statistics
2. W.W.S. Wei (1991) Time Series Analysis: Univariate and Multivariate Methods. Addison Wesley Publishing Company.
3. J. D. Hamilton (1994)Time Series Analysis. Princeton University Press

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 Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics X
2 Acquiring the skills of macro level economic analysis X
3 Acquiring the skills of micro level economic analysis X
4 Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level
5 Learning different approaches on economic and related issues
6 Acquiring the quantitative and/or qualitative techniques in economic analysis X
7 Improving the ability to use the modern software, hardware and/or technological devices X
8 Developing intra-disciplinary and inter-disciplinary team work skills
9 Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning
10 Adopting work ethic and social responsibility
11 Developing the skills of communication.
12 Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs.

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 10 10
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 25 25
Total Workload 141