Probability Theory and Statistics
| Title | Θεωρία Πιθανοτήτων και Στατιστική / Probability Theory and Statistics |
| Code | 020 |
| Faculty | Engineering |
| School | Electrical and Computer Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Dimitris Kugiumtzis |
| Common | No |
| Status | Active |
| Course ID | 600000968 |
Programme of Study: Electrical and Computer Engineering
Registered students: 400
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| CORE | Compulsory Course | 4 | 2 | 6 |
| Academic Year | 2019 – 2020 |
| Class Period | Spring |
| Faculty Instructors | |
| Class ID | 600144699
|
Class Schedule
| Building | Πολυτεχνείο - πτέρυγα Γ (ΤΗΜΜΥ & Τοπογράφων Μηχ.) |
| Floor | Όροφος 1 |
| Hall | Α5 (7) |
| Calendar | Δευτέρα 11:00 έως 13:00 |
| Building | Πολυτεχνείο - πτέρυγα Γ (ΤΗΜΜΥ & Τοπογράφων Μηχ.) |
| Floor | Όροφος 1 |
| Hall | Α5 (7) |
| Calendar | Δευτέρα 18:00 έως 20:00 |
| Building | Πολυτεχνείο - πτέρυγα Γ (ΤΗΜΜΥ & Τοπογράφων Μηχ.) |
| Floor | Όροφος 1 |
| Hall | Α5 (7) |
| Calendar | Παρασκευή 11:00 έως 13:00 |
Course Type 2016-2020
- Background
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600144699
- eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=6010
- Other: http://users.auth.gr/dkugiu/Teach/ElectricEngineer/index.html
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
- English (Instruction, Examination)
Learning Outcomes
Upon successful completion of the course, the students will have a good understanding of the fundamental principles of probability and probability distributions of random variables, as well as their application to problems of engineering. Further, they will be able to do the basic statistical analysis of data of one and two quantities (random variables) in engineering problems. Specifically, they will be able to estimate main statistical characteristics of the variable of interest, such as the mean and variance, reporting the estimation accuracy, as well as the (linear) correlation and regression of two variables of interest.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Work in teams
Course Content (Syllabus)
PROBABILITY THEORY:
Probability space, conditional probability, total probability, Bayes’ theorem. Random variables. Distribution functions of discrete and continuous random variables. Theoretical distributions (binomial, geometric, negative geometric, hypergeometric, Poisson, uniform, normal, exponential). Characteristics and parameters of distributions (mean value, variance, other moments, mode, Tchebycheff inequality). Functions of random variables.
STATISTICS:
Descriptive statistics of data (summary statistics and graphs). Estimation of distribution parameters from observations of a random variable, properties of estimators, the method of moments and the method of maximum likelihood, estimation of confidence interval for the mean, variance and difference of two means. Regression and correlation analysis, simple linear regression.
Keywords
Probability, statistics
Educational Material Types
- Notes
- Slide presentations
- Multimedia
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
Description
Computer programs: A practical lab on the statistical software SPSS is offered.
Multimedia: The interactive educational statistical program VESTAC is presented in the class. Webcasts for the practical lab on the statistical software SPSS are available through the course web page.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 90 | 3 | ✓ | ||
| Laboratory Work | 45 | 1.5 | ✓ | ||
| Exams | 30 | 1 | ✓ | ||
| Topic presentations | 15 | 0.5 | ✓ | ||
| Total | 180 | 6 |
Student Assessment
Description
Written exams: 80% of the final mark (provided that the student has succeeded in at least 50% of the exam questions).
Project on Probability: 10% of the final mark
Project on Statistics (practical essay on the basis of the statistical software SPSS or presentation of a special topic in statistics): 10% of the final mark
Student Assessment methods
- Written Assignment (Formative, Summative)
- Performance / Staging (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
- Report (Formative, Summative)
- Labortatory Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
1. "Πιθανότητες για Μηχανικούς, Μέθοδοι-Εφαρμογές", Γεώργιος Χ. Ζιούτας, εκδόσεις Σοφία, Θεσσαλονίκη 2005 (Κωδικός Βιβλίου στον Εύδοξο: 513)
2. "Στοιχεία Πιθανοθεωρίας", Λεωνίδας Καμαρινόπουλος, εκδόσεις Ζήτη, Θεσσαλονίκη 1993 (Κωδικός Βιβλίου στον Εύδοξο: 11380)
3. Σημειώσεις για το Μέρος Β του μαθήματος, Δημήτρης Κουγιουμτζής, ανατύπωση ΑΠΘ, 2010 (http://users.auth.gr/dkugiu/Teach/ElectricEngineer/index.html)
Last Update
02-12-2020
