COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Multivariate Statistical Analysis * ECMZ   307 5 3 3 5

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction English
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Assoc.Prof.Dr. Hüseyin GÜLER
Instructors
Doç.Dr.HÜSEYİN GÜLER1. Öğretim Grup:A
 
Assistants
Goals
The aim of this course is the building of 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.
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.

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explains Econometric concepts
X
2
Acquires basic Mathematics, Statistics and Operation Research concepts
X
3
Equipped with the foundations of Economics, and develops Economic models
4
Describes the necessary concepts of Business
5
Models problems with Mathematics, Statistics, and Econometrics
6
Estimates the model consistently and analyzes & interprets its results
X
7
Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems
X
8
Collects, edits, and analyzes data
X
9
Uses a package program of Econometrics, Statistics, and Operation Research
X
10
Effectively works, take responsibility, and the leadership individually or as a member of a team
X
11
Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study
X
12
Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied
X
13
Uses Turkish and at least one other foreign language, academically and in the business context
X
14
Good understanding, interpretation, efficient written and oral expression of the people involved
X
15
Improves his/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development
16
Questions traditional approaches and their implementation while developing alternative study programs when required
X
17
Recognizes and implements social, scientific, and professional ethic values
X
18
Follows actuality, and interprets the data about economic and social events
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Motivation: A Review of references and introductory matrix algebra Related chapters of reference books
2 Building the data matrix for multivariate analysis and descriptive statistics Related chapters of reference books
3 Multivariate graphics, standardization and multivariate normal distribution Related chapters of reference books
4 Building the data matrix for multivariate analysis and descriptive statistics Related chapters of reference books
5 Canonical correlation analysis and its applications Related chapters of reference books
6 Dimension Reduction: Factor analysis and its assumptions Related chapters of reference books
7 Dimension Reduction (cont): Factor analysis and its applications Related chapters of reference books
8 Midterm Exam
9 Classification: Clustering analysis and its assumptions Related chapters of reference books
10 Classification (cont): Clustering analysis and its assumptions Related chapters of reference books
11 Classification: Assumptions of discriminant analysis Related chapters of reference books
12 Classification (cont): Applications of discriminant analysis Related chapters of reference books
13 Discussion of papers about multivariate methods Related chapters of reference books
14 Discussion of papers about multivariate methods Related chapters of reference books
15 Discussion of papers about multivariate methods Related chapters of reference books
16-17 Final Exam

Recommended or Required Reading
Textbook
Additional Resources