SEN4016 Multivariate Data AnalysisBahçeşehir UniversityDegree Programs PSYCHOLOGYGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
PSYCHOLOGY
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 develop an interest in the human mind and behavior, to be able to evaluate theories using empirical findings, to understand that psychology is an evidence-based science by acquiring critical thinking skills.
2) To gain a biopsychosocial perspective on human behavior. To understand the biological, psychological, and social variables of behavior.
3) To learn the basic concepts in psychology and the theoretical and practical approaches used to study them (e.g. basic observation and interview techniques).
4) To acquire the methods and skills to access and write information using English as the dominant language in the psychological literature, to recognize and apply scientific research and data evaluation techniques (e.g. correlational, experimental, cross-sectional and longitudinal studies, case studies).
5) To be against discrimination and prejudice; to have ethical concerns while working in research and practice areas.
6) To recognize the main subfields of psychology (experimental, developmental, clinical, cognitive, social and industrial/organizational psychology) and their related fields of study and specialization.
7) To acquire the skills necessary for analyzing, interpreting and presenting the findings as well as problem posing, hypothesizing and data collection, which are the basic elements of scientific studies.
8) To gain the basic knowledge and skills necessary for psychological assessment and evaluation.
9) To acquire basic knowledge of other disciplines (medicine, genetics, biology, economics, sociology, political science, communication, philosophy, anthropology, literature, law, art, etc.) that will contribute to psychology and to use this knowledge in the understanding and interpretation of psychological processes.
10) To develop sensitivity towards social problems; to take responsibility in activities that benefit the field of psychology and society.
11) To have problem solving skills and to be able to develop the necessary analytical approaches for this.
12) To be able to criticize any subject in business and academic life and to be able to express their thoughts.