ECMZ307 Multivariate Statistical Analysis

5 ECTS - 3-0 Duration (T+A)- 5. Semester- 3 National Credit

Information

Code ECMZ307
Name Multivariate Statistical Analysis
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 Goal

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