ECTS - Multi Dimensional Data Modeling
Multi Dimensional Data Modeling (ECON553) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Multi Dimensional Data Modeling | ECON553 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Social Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture. |
| Course Lecturer(s) |
|
| 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;
|
| 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 | Markov Chain Models | WWSW, KSS and JDH |
| 7 | Smooth Transition and Threshold Models | Lecture notes available |
| 8 | Frequency Domain: Fourier Function | WWSW, KSS and JDH |
| 9 | Periodgram | WWSW |
| 10 | Asymptotic Concepts in N and T | JDH |
| 11 | Ridge regression and Lasso estimator | Lecture notes available |
| 12 | Functional Regression Analysis | Lecture notes available |
| 13 | Information Accumulated Multilayer Models (IAM) | Lecture notes available |
| 14 | 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 | 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 | To compare main microeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 2 | To compare main macroeconomic theories, approaches and make a critical evaluation of each | X | ||||
| 3 | To apply mathematical modeling | X | ||||
| 4 | To employ statistical and econometric tools in analyzing an economic phenomena | X | ||||
| 5 | To analyze the main economic indicators and comment on them | X | ||||
| 6 | To acquire theoretical knowledge through literature survey and derive empirically confirmable hypothesis | X | ||||
| 7 | To make a research design and carry it out within predetermined time frames | X | ||||
| 8 | To be able to develop new approaches for complex problems in applied economics and/or apply statistical/econometric tools to new areas/problems | X | ||||
| 9 | To formulate and present policy recommendations based on academic research | X | ||||
| 10 | To combine economic knowledge with other disciplines in order to solve problems requiring scientific expertise | X | ||||
| 11 | To use information technology effectively | X | ||||
| 12 | To continue learning and undertake advanced research independently | 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 | ||