NURSING (ENGLISH)
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	Fall	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)	"To plan and assess nursing care within a holistic approach, in accordance with theoretical and evidence-based practices. "
2)	To act in accordance with ethical principles and values in Nursing practices.
3)	To use life-long learning, problem-solving and critical thinking skills.
4)	To use Nursing models/theories in health promotion, protection and care.
5)	To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach.
6)	"To have skills for training and consulting according to health education needs of individual, family and the community. "
7)	"To be sensitive to health problems of the community and and to able to offer solutions. "
8)	"To be able to use interpersonal and intercultural communication skills effectively in Nursing pratices. "
9)	"To be able to use healthcare/information technologies in Nursing practice and research. "
10)	To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively.
11)	To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level.
12)	To take responsibility and lead in events in order to contribute to health services and Nursing profession.