ECONOMICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
SEN4016	Multivariate Data Analysis	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Prof. Dr. MEHMET ALPER TUNGA
Recommended Optional Program Components:	None.
Course Objectives:	The students will have the ability of applying specific techniques included in multivariate analysis such as principle component analysis, factor analysis, linear regression to specific problems.

Learning Outcomes

The students who have succeeded in this course;
1. Describe multivariate data analysis concepts
2. Define the properties and limitations of PCA and compute PCA through different ways
3. Describe the types of factoring and factor computation
4. Define metric and non-metric scales
5. Describe simple and multiple correspondence analysis and chi squared distances
6. Define variations of MANOVA
7. Evaluate regression coefficients, parameter estimation, hypothesis testing
8. Describe deduction, induction, estimation, tests, correlation
9. Define univariate and multivariate filters

Course Content

The course content is composed of principle component analysis (pca), factor analysis, multidimensional scaling, correspondence analysis, multivariate analysis of variance (manova), multiple linear regression, statistical inference, feature subset selection.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction
2)	Principle Component Analysis (PCA)
3)	Principle Component Analysis (PCA)
4)	Factor Analysis
5)	Factor Analysis
6)	Multidimensional Scaling
7)	Correspondence Analysis
8)	Multivariate Analysis of Variance (MANOVA)
9)	Multiple Linear Regression
10)	Multiple Linear Regression
11)	Statistical Inference
12)	Statistical Inference
13)	Feature Subset Selection
14)	Feature Subset Selection

Sources

Course Notes / Textbooks:	Multivariate Data Analysis, 7/E, Joseph F. Hair, Jr, William C. Black, Barry J. Babin, Rolph E. Anderson, Pearson, 2010, 9780138132637
References:	Yok - None.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	4	% 20
Homework Assignments	2	% 10
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	4	5	20
Homework Assignments	2	5	10
Quizzes	4	3	12
Midterms	1	15	15
Final	1	17	17
Total Workload			116

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	As a world citizen, she is aware of global economic, political, social and ecological developments and trends.
2)	He/she is equipped to closely follow the technological progress required by global and local dynamics and to continue learning.
3)	Absorbs basic economic principles and analysis methods and uses them to evaluate daily events.
4)	Uses quantitative and statistical tools to identify economic problems, analyze them, and share their findings with relevant stakeholders.
5)	Understands the decision-making stages of economic units under existing constraints and incentives, examines the interactions and possible future effects of these decisions.
6)	Comprehends new ways of doing business using digital technologies. and new market structures.
7)	Takes critical approach to economic and social problems and develops analytical solutions.
8)	Has the necessary mathematical equipment to produce analytical solutions and use quantitative research methods.
9)	In the works he/she contributes, observes individual and social welfare together and with an ethical perspective.
10)	Deals with economic problems with an interdisciplinary approach and seeks solutions by making use of different disciplines.
11)	Generates original and innovative ideas in the works she/he contributes as part of a team.