CIVIL ENGINEERING | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
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. |
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. |
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 |
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. |
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 |
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. |
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 |
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 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Adequate knowledge in mathematics, science and civil engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems. | |
2) | Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | |
3) | Ability to design a complex system, process, structural and/or structural members to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose. | |
4) | Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in civil engineering applications; ability to use civil engineering technologies effectively. | |
5) | Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or civil engineering research topics. | |
6) | Ability to work effectively within and multi-disciplinary teams; individual study skills. | |
7) | Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. | |
8) | Awareness of the necessity of lifelong learning; ability to access information to follow developments in civil engineering technology. | |
9) | To act in accordance with ethical principles, professional and ethical responsibility; having awareness of the importance of employee workplace health and safety. | |
10) | Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development. | |
11) | Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of civil engineering solutions. |