MULTIVARIATE STATISTICS
| Title | ΣΤΑΤΙΣΤΙΚΗ ΠΟΛΛΩΝ ΜΕΤΑΒΛΗΤΩΝ / MULTIVARIATE STATISTICS |
| Code | 208 |
| Faculty | Engineering |
| School | Mechanical Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter |
| Coordinator | Sofia Panagiotidou |
| Common | Yes |
| Status | Active |
| Course ID | 20000307 |
Programme of Study: UPS of School of Mechanical Engineering
Registered students: 86
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Energy | Elective Courses belonging to the other | 7 | 4 | 5 |
| Design and Structures | Elective Courses belonging to the other | 7 | 4 | 5 |
| Industrial Management | Compulsory Course belonging to the selected specialization (Compulsory Specialization Course) | 7 | 4 | 5 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors |
|
| Weekly Hours | 4 |
| Total Hours | 52 |
| Class ID | 600287768
|
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600287768
- At the Website of the School: https://qa.auth.gr/el/class/1/600260540
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=4360
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
The course "Statistics" is not formally a prerequisite but sufficient knowledge of its content is essential for the effective understanding of the concepts in "Multivariate Statistics".
Learning Outcomes
Upon successful completion of the course, the student will be able to:
1.Understand basic concepts of probability theory
2.Understand the statistical analysis methods in problems where more than one random variables are involved
3.Recognize the importance of statistical experiments
4.Apply computer software (SPSS, Data analysis, Minitab) for statistical data analysis
5.Interpret the results of statistical inference
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Work autonomously
- Advance free, creative and causative thinking
Course Content (Syllabus)
Two and higher-dimensional random variables: joint, marginal and conditional distributions. Covariance and correlation. Independent random variables, sums of independent random variables. The bivariate normal distribution.
Analysis of variance: the fixed and random effects models for one factor.
Design of statistical experiments: factorial and fractional factorial experiments, design and statistical analysis.
Simple and multiple linear regression, nonlinear regression, correlation.
Keywords
Regression, Correlation, Design and Analysis of Experiments
Educational Material Types
- Notes
- Slide presentations
- Book
- Computer software
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
Utilization of specialized computer software for problem solving.
Posting of announcements, notes and information regarding the course at eLearning (https://elearning.auth.gr/course/view.php?id=4360).
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 52 | 1.7 | ✓ | ||
| Reading Assigment | 62 | 2.1 | ✓ | ✓ | |
| Interactive Teaching in Information Center | 6 | 0.2 | ✓ | ||
| Written assigments | 25 | 0.8 | ✓ | ||
| Exams | 5 | 0.2 | ✓ | ||
| Total | 150 | 5 |
Student Assessment
Description
The final grade M is a combination of the grades in the final written examination (T), the midterm examination (Π) and the project/homework (E) as follows:
• If either Τ < 4,5 or (Τ+Π)/2 < 4, then the final grade is Μ = (0,8)Τ.
• In every other case the final grade is Μ = max {(0,6)Τ + (0,3)Π + (0,2)Ε, (0,8)T}.
Student Assessment methods
- Written Exam with Short Answer Questions (Summative)
- Written Exam with Extended Answer Questions (Summative)
- Written Assignment (Summative)
- Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
1. Βιβλίο [11368]: Στατιστικός έλεγχος ποιότητας, Ταγαράς Γιώργος Ν.
2. Βιβλίο [15310]: Στατιστική για οικονομικά και διοίκηση επιχειρήσεων, Keller Gerald
3. Βιβλίο [112696237]: Στατιστική 5η έκδοση, Ιωάννης Χαλικιάς
4. Βιβλίο [112691973]: Πιθανότητες και Στατιστική για Μηχανικούς, 2η Έκδοση, Μυλωνάς Νίκος - Παπαδόπουλος Βασίλειος
Additional bibliography for study
- Antony, J., Kaye, M., Experimental Quality, Kluwer, 1999.
- Cobb, G.W., Introduction to Design and Analysis of Experiments, Springer, 2002.
- Montgomery, D.C., Design and Analysis of Experiments, Wiley, 2008.
- Montgomery, D.C., Runger, G.C., Applied Statistics and Probability for Engineers, Wiley, 2006.
- Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, Wiley, 2007.
Last Update
22-10-2025
