Advanced Topics in Statistics (ΣΕΕ19): Διαφορά μεταξύ των αναθεωρήσεων
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* [[Ειδικά Θέματα Στατιστικής (ΣEE19)|Ελληνική Έκδοση]] | * [[Ειδικά Θέματα Στατιστικής (ΣEE19)|Ελληνική Έκδοση]] | ||
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=== General === | === General === |
Τελευταία αναθεώρηση της 16:39, 15 Ιουνίου 2023
- Ελληνική Έκδοση
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General
School | School of Science |
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Academic Unit | Department of Mathematics |
Level of Studies | Graduate |
Course Code | ΣΣΕ19 |
Semester | 2 |
Course Title |
Advanced Topics in Statistics |
Independent Teaching Activities | Lectures-Laboratory (Weekly Teaching Hours: 3, Credits: 7.5) |
Course Type |
Specialized general knowledge |
Prerequisite Courses | - |
Language of Instruction and Examinations | Greek |
Is the Course Offered to Erasmus Students |
Yes (in English, reading Course) |
Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
Learning outcomes |
The purpose of this advanced course is to enrich students' knowledge with current advanced topics of statistical methodology and theory that are not closely related to other courses of the subject. Moreover, this course would be characterized by a close relationship with other areas of mathematics and computing, among others, and the aim is to be characterized by an interdisciplinary character. In the learning outcomes is included the familiarization of the students, by means of this course, with an interdisciplinary type of thinking for solving problems of the real world. |
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General Competences |
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Syllabus
The precise content of this course may vary from time to time, but it will consist of selected, advanced topics of contemporary research interest in statistical methodology, depending on both demands from students and the availability of appropriate course leaders. Examples include parametric lifetime modeling, experimental design, extreme value statistics, advanced stochastic simulation, graphical modeling, statistics quality control etc. The course will be of interest to students who want to develop their basic knowledge of statistics methodology. See the specific semester page for a more detailed description of the course.
Teaching and Learning Methods - Evaluation
Delivery | Classroom (face-to-face) | ||||||||||
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Use of Information and Communications Technology |
Use of ICT in communication with students | ||||||||||
Teaching Methods |
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Student Performance Evaluation |
Final written exam in Greek (in case of Erasmus students in English). |
Attached Bibliography
Θα καθορίζεται από τον διδάσκοντα / Will be determined by the teacher