SEN4016 Multivariate Data AnalysisBahçeşehir UniversityDegree Programs ARCHITECTUREGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
ARCHITECTURE
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
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) Using the theoretical/conceptual and practical knowledge acquired for architectural design, design activities and research.
2) Identifying, defining and effectively discussing aesthetic, functional and structural requirements for solving design problems using critical thinking methods.
3) Being aware of the diversity of social patterns and user needs, values and behavioral norms, which are important inputs in the formation of the built environment, at local, regional, national and international scales.
4) Gaining knowledge and skills about architectural design methods that are focused on people and society, sensitive to natural and built environment in the field of architecture.
5) Gaining skills to understand the relationship between architecture and other disciplines, to be able to cooperate, to develop comprehensive projects; to take responsibility in independent studies and group work.
6) Giving importance to the protection of natural and cultural values in the design of the built environment by being aware of the responsibilities in terms of human rights and social interests.
7) Giving importance to sustainability in the solution of design problems and the use of natural and artificial resources by considering the social, cultural and environmental issues of architecture.
8) Being able to convey and communicate all kinds of conceptual and practical thoughts related to the field of architecture by using written, verbal and visual media and information technologies.
9) Gaining the ability to understand and use technical information about building technology such as structural systems, building materials, building service systems, construction systems, life safety.
10) Being aware of legal and ethical responsibilities in design and application processes.