Special Topics in Statistics (MAE837): Διαφορά μεταξύ των αναθεωρήσεων

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=== Attached Bibliography ===
=== Attached Bibliography ===
Since the precise contents of this course may vary from occasion to occasion, depending on both demands from students and the availability of instructors, for the bibliography see the specific semester page. For the next academic year 2018-2019 the bibliography is:
 
* Καρλής Δημήτρης (2005). Πολυμεταβλητή στατιστική ανάλυση. Εκδόσεις Σταμούλη.
See [https://service.eudoxus.gr/public/departments#20 Eudoxus].
* DAVID J. BARTHOLOMEW, FIONA STEELE, IRINI MOUSTAKI, JANE I. GALBRAITH (2011). Ανάλυση πολυμεταβλητών τεχνικών στις κοινωνικές επιστήμες. Εκδόσεις Κλειδάριθμος ΕΠΕ.

Αναθεώρηση της 17:11, 23 Ιουλίου 2022

Undergraduate Courses Outlines - Department of Mathematics

General

School

School of Science

Academic Unit

Department of Mathematics

Level of Studies

Undergraduate

Course Code

ΜΑΕ837

Semester

8

Course Title

Special Topics in Statistics

Independent Teaching Activities

Lectures (Weekly Teaching Hours: 3, Credits: 6)

Course Type

Special Background

Prerequisite Courses -
Language of Instruction and Examinations

Greek

Is the Course Offered to Erasmus Students

Yes (in English, reading Course)

Course Website (URL) -

Learning Outcomes

Learning outcomes

Students will become familiar with the themes in question and develop knowledge of statistical methods, and will also learn how the methodology becomes relevant in certain application areas. Students will learn a specialized field of statistics not covered by any ordinary course.

General Competences
  • Working independently
  • Decision-making
  • Production of free, creative and inductive thinking
  • Criticism and self-criticism.

Syllabus

The precise contents of this course may vary from occasion to occasion, but will consist of selected themes of contemporary research interest in statistics 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.
For the next academic year the syllabus of the course is the following: Multivariate distributions: basic properties. Multivariate normal distribution: properties and estimation. Brief review of multivariate methods of statistical analysis: Principal Components, Factor Analysis, MANOVA, Discriminant Analysis.

Teaching and Learning Methods - Evaluation

Delivery

Classroom (face-to-face)

Use of Information and Communications Technology -
Teaching Methods
Activity Semester Workload
Lectures 39
Working independently 78
Exercises-Homeworks 33
Course total 150
Student Performance Evaluation

Final written exam in Greek (in case of Erasmus students in English) which concentrates on the solution of problems which are motivated by the main themes of the course.

Attached Bibliography

See Eudoxus.