TÜRKÇE
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Information
| Code | ECMZ307 |
| Name | Multivariate Statistical Analysis |
| Term | 2024-2025 Academic Year |
| Semester | 5. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. HÜSEYİN GÜLER |
| Course Instructor |
Dr. Öğr. Üyesi Sibel ÖRK ÖZEL
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to bring the knowledge of building the data matrix for multivariate analysis, choosing the most suitable method for the data, and application of the proper technique once the assumptions are verified.
Course Content
The course content covers the building of multivariate data, which includes understanding, preparing and transforming of the data, comparing the methods related to dimension reduction and classification, assumptions and applications of multivariate techniques.
Course Precondition
None
Resources
“Multivariate Data Analysis, A Global Perspective, Seventh Edition” by Joseph F. Hair, Jr., William C. Black, Barry J. Babin, Rolph E. Anderson, Pearson, 2010.
Notes
“Using Multivariate Statistics, Tabachnick, Fidell, QA278.T33 2007”. “Applied Multivariate Statistical Analysis, Johnson & Wichern, QA278J64 2002”. “An introduction to multivariate statistical analysis, Wilbur, QA278A54 2003”.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains multivariate data |
| LO02 | Builds the data matrix |
| LO03 | Knows dimension reduction techniques |
| LO04 | Explains assumptions of dimension reduction techniques |
| LO05 | Knows classification methods |
| LO06 | Explains assumptions of classification methods |
| LO07 | Discriminates the most proper analysis technique for the data being analyzed |
| LO08 | Uses a package program to analyze each technique |
| LO09 | Appropriately interprets findings of analysis |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the basic concepts and theorems in the fields of Econometrics, Statistics and Operations research | 4 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Acquires basic Mathematics, Statistics and Operation Research concepts | 5 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Describes the necessary concepts of Business | |
| PLO04 | Beceriler - Bilişsel, Uygulamalı | Equipped with the foundations of Economics, and develops Economic models | |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 5 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Has the ability to analyze/interpret at the conceptual level to develop solutions to problems | 3 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Collects/analyses data | 5 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Interprets the results analyzed with the model | 5 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Combines the information obtained from different sources within the framework of academic rules in a field which does not research | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | It develops traditional approaches, practices and methods into new working methods when it deems necessary | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | |
| PLO12 | Yetkinlikler - Öğrenme Yetkinliği | In addition to herself/himself professional development, constantly improves in scientific, cultural, artistic and social fields in line with interests and abilities | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it follows the current developments in the field / constantly renews itself | |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research | 4 |
| PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses Turkish and at least one other foreign language, academically and in the business context | |
| PLO16 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | |
| PLO17 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on current economic and social issues | |
| PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Motivation: A Review of references and introductory matrix algebra | Reference book - Chapter 1 | Öğretim Yöntemleri: Anlatım |
| 2 | Building the data matrix for multivariate analysis and descriptive statistics | Reference book - Chapter 2 | Öğretim Yöntemleri: Anlatım, Deney / Laboratuvar |
| 3 | Multivariate graphics, standardization and multivariate normal distribution | Reference book - Chapter 2 | Öğretim Yöntemleri: Anlatım, Deney / Laboratuvar, Problem Çözme |
| 4 | Exploring data before the analysis | Reference book - Chapter 2 | Öğretim Yöntemleri: Anlatım, Deney / Laboratuvar |
| 5 | Canonical correlation analysis and its applications | Reference book - Chapter 5 | Öğretim Yöntemleri: Anlatım, Deney / Laboratuvar, Problem Çözme |
| 6 | Dimension Reduction: Factor analysis and its assumptions | Reference book - Chapter 3 | Öğretim Yöntemleri: Anlatım, Örnek Olay, Deney / Laboratuvar |
| 7 | Dimension Reduction (cont): Factor analysis and its applications | Reference book - Chapter 3 | Öğretim Yöntemleri: Anlatım, Örnek Olay, Deney / Laboratuvar, Problem Çözme |
| 8 | Mid-Term Exam | General review for the midterm exam | Ölçme Yöntemleri: Yazılı Sınav |
| 9 | Classification: Clustering analysis and its assumptions | Reference book - Chapter 9 | Öğretim Yöntemleri: Anlatım, Deney / Laboratuvar |
| 10 | Classification (cont): Clustering analysis and its assumptions | Reference book - Chapter 9 | Öğretim Yöntemleri: Anlatım, Örnek Olay, Deney / Laboratuvar, Problem Çözme |
| 11 | Classification: Assumptions of discriminant analysis | Reference book - Chapter 7 | Öğretim Yöntemleri: Anlatım |
| 12 | Classification (cont): Applications of discriminant analysis | Reference book - Chapter 7 | Öğretim Yöntemleri: Anlatım, Örnek Olay, Deney / Laboratuvar, Problem Çözme |
| 13 | Discussion of papers about canonical correlation and factor analysis | Related chapters of reference books and academic databases | Öğretim Yöntemleri: Grup Çalışması, Proje Temelli Öğrenme |
| 14 | Discussion of papers about clustering analysis | Related chapters of reference books and academic databases | Öğretim Yöntemleri: Grup Çalışması, Proje Temelli Öğrenme |
| 15 | Discussion of papers about discriminant analysis | Related chapters of reference books and academic databases | Öğretim Yöntemleri: Grup Çalışması, Proje Temelli Öğrenme |
| 16 | Term Exams | General review for the final exam | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | General review for the final exam | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||