Linear Models (ΣΕΕ2): Διαφορά μεταξύ των αναθεωρήσεων
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(Νέα σελίδα με '=== General === {| class="wikitable" |- ! School | School of Science |- ! Academic Unit | Department of Mathematics |- ! Level of Studies | Graduate |- ! Course Code | ΣΣΕ2 |- ! Semester | 1 |- ! Course Title | Linear Models |- ! Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |- ! Course Type | Special Background |- ! Prerequisite Courses | - |- ! Language of Instruction and Examinations | Greek |- ! Is the Course Offered t...') |
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=== General === | === General === | ||
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|- | |- | ||
! Course Type | ! Course Type | ||
| | | | ||
Specialized general knowledge | |||
|- | |- | ||
! Prerequisite Courses | ! Prerequisite Courses | ||
| Γραμμή 37: | Γραμμή 42: | ||
|- | |- | ||
! Course Website (URL) | ! Course Website (URL) | ||
| | | See [https://ecourse.uoi.gr/ eCourse], the Learning Management System maintained by the University of Ioannina. | ||
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{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
! Learning | ! Learning Outcomes | ||
| | | | ||
By the end of the course students are expected to demonstrate: | |||
* A strong foundation in simple linear, multiple regression and in the one- and two-way analysis of variance as well as in extending these concepts, | |||
* Deep knowledge of the main assumptions of the general linear model and their implications when violated, | |||
* How to conduct diagnostics and correct for the violation of the assumptions of the general linear model, | |||
* How to interpret various coefficients and in general how to analyze data with linear models, | |||
* How to deal with multicollinearity effects, missing data e.t.c.. | |||
|- | |- | ||
! General Competences | ! General Competences | ||
| | | | ||
* Working independently | |||
* Decision-making | |||
* Adapting to new situations | |||
* Production of free, creative and inductive thinking | |||
* Synthesis of data and information, with the use of the necessary technology | |||
* Working in an interdisciplinary environment | |||
|} | |} | ||
=== Syllabus === | === Syllabus === | ||
General Linear Model of full Rank | The General Linear Model of full Rank and its statistical properties. Multiple Regression Analysis. Hypothesis tests, diagnostic measures and residual analysis. Variable selection. Models of non full rank. Estimable functions, One and two-way analysis of variance with equal and unequal numbers per cell. | ||
=== Teaching and Learning Methods - Evaluation === | === Teaching and Learning Methods - Evaluation === | ||
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| 39 | | 39 | ||
|- | |- | ||
| | | Independent study | ||
| | | 70 | ||
|- | |- | ||
| | | Study and analysis of bibliography, Fieldwork | ||
| | | 78.5 | ||
|- | |- | ||
| Course total | | Course total | ||
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=== Attached Bibliography === | === Attached Bibliography === | ||
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Τελευταία αναθεώρηση της 16:39, 15 Ιουνίου 2023
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General
| School | School of Science |
|---|---|
| Academic Unit | Department of Mathematics |
| Level of Studies | Graduate |
| Course Code | ΣΣΕ2 |
| Semester | 1 |
| Course Title | Linear Models |
| Independent Teaching Activities | Lectures (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 |
By the end of the course students are expected to demonstrate:
|
|---|---|
| General Competences |
|
Syllabus
The General Linear Model of full Rank and its statistical properties. Multiple Regression Analysis. Hypothesis tests, diagnostic measures and residual analysis. Variable selection. Models of non full rank. Estimable functions, One and two-way analysis of variance with equal and unequal numbers per cell.
Teaching and Learning Methods - Evaluation
| Delivery | Face-to-face | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Use of Information and Communications Technology | Use of ICT in communication with students | ||||||||||
| Teaching Methods |
| ||||||||||
| Student Performance Evaluation | Final written exam in Greek (in case of Erasmus students in English). |
Attached Bibliography
- Καρακώστας, Κ. (2002). Γραμμικά Μοντέλα: Παλινδρόμηση και Ανάλυση Διακύμανσης. Πανεπιστήμιο Ιωαννίνων.
- Λουκάς, Σ. (2014). Γενικό Γραμμικό Μοντέλο. Πανεπιστήμιο Ιωαννίνων.
- Οικονόμου, Π. και Καρώνη, Χ. (2010). Στατιστικά Μοντέλα Παλινδρόμησης, Εκδόσεις Συμεών.
- Draper, N.R. and H. Smith, (1998). Applied Regression Analysis, Third Edition, Wiley,
- Searle, S.R., (1997). Linear Models, Wiley Classics Library, Wiley,
- Seber, G.A.F. and A.J. Lee, (2003). Linear Regression Analysis, 2nd Edition, Wiley.