Time Series

Course Information
TitleΧΡΟΝΙΚΕΣ ΣΕΙΡΕΣ / Time Series
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorKostas Loumponias
Course ID40000530

Programme of Study: UPS of School of Mathematics (2014-today)

Registered students: 167
OrientationAttendance TypeSemesterYearECTS
CoreElective CoursesSpring-5

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Instructors from Other Categories
Weekly Hours3
Class ID
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
Upon successful completion of the course, students will: - be able to recognize the qualitative characteristics of time series, e.g. trend, periodicity etc. - have a comprehensive theoretical background on the basic methods of time series analysis - have knowledge and critical understanding of the key properties of AR, MA, ARMA and ARIMA models - can fit time series data to linear stochastic models - have a comprehensive theoretical background on the basic methods of time series prediction
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Appreciate diversity and multiculturality
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Time series characteristics, στατιοναριτυ, autocorrelation function, linear stochastic models: AR (p), MA (q), ARMA (p, q), finding the order of a linear model, non-stationary ARIMA models (p, d, q), methodology of Box & Jenkins, methods of predicting time series.
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
Course Organization
Reading Assigment401.3
Student Assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Exam with Extended Answer Questions (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Course Bibliography (Eudoxus)
- Εφαρμοσμένη Στατιστική, Ε. Μπόρα-Σέντα, Π. Μωυσιάδης, Ζήτη, 1990 - Σύγχρονες Μέθοδοι Ανάλυσης Χρονολογικών Σειρών, Σ. Δημέλη, Κριτική, 2013
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