Linear Models (ΣΕΕ2): Διαφορά μεταξύ των αναθεωρήσεων
Από Wiki Τμήματος Μαθηματικών
| Γραμμή 47: | Γραμμή 47: | ||
{| class="wikitable" | {| class="wikitable" | ||
|- | |- | ||
! | ! | ||
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 | |||
|} | |} | ||
Αναθεώρηση της 22:31, 27 Οκτωβρίου 2022
Graduate Courses Outlines - Department of Mathematics
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
|
By the end of the course students are expected to demonstrate:
| |
|---|---|
| General Competences |
|
Syllabus
General Linear Model of full Rank, Multiple Regression Analysis, Analysis of residuals-Diagnostics, Selection of Variables, Two way analysis of variance with equal and unequal numbers per cell. Models of non full rank.
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.