SEN4016 Multivariate Data AnalysisBahçeşehir UniversityDegree Programs PHYSIOTHERAPY AND REHABILITATION (TURKISH)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
PHYSIOTHERAPY AND REHABILITATION (TURKISH)
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) To have theoretical and practical knowledge required to fulfill professional roles and functions of Physiotherapy and Rehabilitation field. 2
2) To act in accordance with ethical principles and values in professional practice. 1
3) To use life-long learning, problem-solving and critical thinking skills. 4
4) To define evidence-based practices and determine problem solving methods in Physiotherapy and Rehabilitation practices, using theories in health promotion, protection and care. 1
5) To take part in research, projects and activities within sense of social responsibility and interdisciplinary approach. 3
6) To have skills for training and consulting according to health education needs of individual, family and the community. 1
7) To be sensitive to health problems of the community and to be able to offer solutions. 3
8) To be able to use skills for effective communication. 5
9) To be able to select and use modern tools, techniques and modalities in Physiotherapy and Rehabilitation practices; to be able to use health information technologies effectively. 1
10) To be able to search for literature in health sciences databases and information sources to access to information and use the information effectively. 1
11) To be able to monitor occupational information using at least one foreign language, to collaborate and communicate with colleagues at international level. 1
12) To be a role model with contemporary and professional identity. 4